extract: 2024-08-01-jmcp-glp1-persistence-adherence-commercial-populations

Pentagon-Agent: Ganymede <F99EBFA6-547B-4096-BEEA-1D59C3E4028A>

domains/health/GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035.md

@@ -17,6 +17,12 @@ But the economics are structurally inflationary. Meta-analyses show patients reg
 
 The competitive dynamics (Lilly vs. Novo vs. generics post-2031) will drive prices down, but volume growth more than offsets price compression. GLP-1s will be the single largest driver of pharmaceutical spending growth globally through 2035.
 
+
+### Additional Evidence (extend)
+*Source: [[2024-08-01-jmcp-glp1-persistence-adherence-commercial-populations]] | Added: 2026-03-15 | Extractor: anthropic/claude-sonnet-4.5*
+
+Real-world persistence data from 125,474 commercially insured patients shows the chronic use model fails not because patients choose indefinite use, but because most cannot sustain it: only 32.3% of non-diabetic obesity patients remain on GLP-1s at one year, dropping to approximately 15% at two years. This creates a paradox for payer economics—the "inflationary chronic use" concern assumes sustained adherence, but the actual problem is insufficient persistence. Under capitation, payers pay for 12 months of therapy ($2,940 at $245/month) for patients who discontinue and regain weight, capturing net cost with no downstream savings from avoided complications. The economics only work if adherence is sustained AND the payer captures downstream benefits—with 85% discontinuing by two years, the downstream cardiovascular and metabolic savings that justify the cost never materialize for most patients.
+
 ---
 
 Relevant Notes:

domains/health/glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md

@@ -0,0 +1,58 @@
+---
+type: claim
+domain: health
+description: "Two-year real-world data shows only 15% of non-diabetic obesity patients remain on GLP-1s, meaning most patients discontinue before downstream health benefits can materialize to offset drug costs"
+confidence: likely
+source: "Journal of Managed Care & Specialty Pharmacy, Real-world Persistence and Adherence to GLP-1 RAs Among Obese Commercially Insured Adults Without Diabetes, 2024-08-01"
+created: 2026-03-11
+depends_on: ["GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035"]
+---
+
+# GLP-1 persistence drops to 15 percent at two years for non-diabetic obesity patients undermining chronic use economics
+
+Real-world claims data from 125,474 commercially insured patients initiating GLP-1 receptor agonists for obesity (without type 2 diabetes) reveals a persistence curve that fundamentally challenges the economic model: 46.3% remain on treatment at 180 days, 32.3% at one year, and approximately 15% at two years.
+
+This creates a paradox for payer economics. The "chronic use inflation" concern assumes patients stay on GLP-1s indefinitely at $2,940+ annually. But the actual problem may be insufficient persistence: under capitation, a Medicare Advantage plan pays for 12 months of GLP-1 therapy for a patient who discontinues and regains weight—net cost with no downstream savings from avoided complications.
+
+The economics only work if adherence is sustained AND the payer captures downstream benefits. With 85% of non-diabetic patients discontinuing by two years, the downstream cardiovascular and metabolic savings that justify the cost never materialize for most patients.
+
+## Evidence
+
+**Persistence rates for non-diabetic obesity patients:**
+- 180 days: 46.3%
+- 1 year: 32.3%
+- 2 years: ~15%
+
+**Comparison with diabetic patients:**
+- Non-diabetic patients: 67.7% discontinue within 1 year
+- Diabetic patients: 46.5% discontinue within 1 year (better persistence due to stronger clinical indication)
+- Danish registry data: 21.2% of T2D patients discontinue within 12 months; ~70% discontinue within 2 years
+
+**Drug-specific variation:**
+- Semaglutide: 47.1% persistence at 1 year (highest)
+- Liraglutide: 19.2% persistence at 1 year (lowest)
+- Formulation matters: oral formulations may improve adherence by removing injection barrier
+
+**Key discontinuation factors:**
+- Insufficient weight loss (clinical disappointment)
+- Income level (lower income → higher discontinuation, suggesting affordability/access barriers)
+- Adverse events (primarily GI side effects)
+- Insurance coverage changes
+
+**Critical nuance from source:** "Outcomes approach trial-level results when focusing on highly adherent patients. The adherence problem is not that the drugs don't work—it's that most patients don't stay on them."
+
+## Challenges
+
+This data comes from commercially insured populations (younger, fewer comorbidities than Medicare). Medicare populations may show different persistence patterns due to higher disease burden and stronger clinical indications. However, Medicare patients also face higher cost-sharing barriers, which could worsen adherence.
+
+No data yet on whether payment model affects persistence—does being in an MA plan with care coordination improve adherence vs. fee-for-service? This is directly relevant to value-based care design.
+
+---
+
+Relevant Notes:
+- [[GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035]]
+- [[value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk]]
+- [[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]
+
+Topics:
+- domains/health/_map

domains/health/lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md

@@ -0,0 +1,48 @@
+---
+type: claim
+domain: health
+description: "Income level correlates with GLP-1 discontinuation rates in commercially insured populations, indicating that cost-sharing and affordability barriers drive adherence as much as clinical factors like side effects or insufficient weight loss"
+confidence: experimental
+source: "Journal of Managed Care & Specialty Pharmacy, Real-world Persistence and Adherence to GLP-1 RAs Among Obese Commercially Insured Adults Without Diabetes, 2024-08-01"
+created: 2026-03-11
+---
+
+# Lower-income patients show higher GLP-1 discontinuation rates suggesting affordability not just clinical factors drive persistence
+
+Among the factors associated with GLP-1 discontinuation in commercially insured populations, income level emerges as a significant predictor: lower-income patients show higher discontinuation rates even when controlling for other factors.
+
+This is notable because the study population is commercially insured—meaning all patients have coverage. The income effect suggests that cost-sharing (copays, deductibles) creates an affordability barrier even within insured populations. For Medicare populations with higher cost-sharing and lower average incomes, this barrier may be substantially worse.
+
+The implication for value-based care design: reducing patient cost-sharing for GLP-1s (through zero-copay programs or coverage carve-outs) may improve persistence enough to make the downstream ROI positive. The relevant question is not "does the drug work?" but "can patients afford to stay on it long enough for it to work?"
+
+## Evidence
+
+**Key discontinuation factors identified:**
+- Insufficient weight loss (clinical disappointment)
+- **Income level (lower income → higher discontinuation)**
+- Adverse events (GI side effects)
+- Insurance coverage changes
+
+The source notes income as a factor but does not provide the specific discontinuation rate by income quartile. This limits the strength of the claim to experimental confidence.
+
+**Context:**
+- Study population: commercially insured adults (younger, higher income than Medicare)
+- Even within this relatively advantaged population, income predicts discontinuation
+- Medicare populations face higher cost-sharing (Part D coverage gap, higher average out-of-pocket costs)
+
+**Mechanism hypothesis:**
+At $245/month list price, even modest copays ($50-100/month) create a sustained affordability barrier. Patients may initiate treatment but discontinue when the monthly cost becomes unsustainable relative to household budget.
+
+## Challenges
+
+The source does not provide granular income-stratified discontinuation rates, so the magnitude of the effect is unclear. It's possible income is a proxy for other factors (health literacy, access to care coordination, baseline health status) rather than affordability per se.
+
+---
+
+Relevant Notes:
+- [[GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035]]
+- [[value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk]]
+- [[SDOH interventions show strong ROI but adoption stalls because Z-code documentation remains below 3 percent and no operational infrastructure connects screening to action]]
+
+Topics:
+- domains/health/_map

domains/health/semaglutide-achieves-47-percent-one-year-persistence-versus-19-percent-for-liraglutide-showing-drug-specific-adherence-variation-of-2-5x.md

@@ -0,0 +1,40 @@
+---
+type: claim
+domain: health
+description: "Within the GLP-1 class, semaglutide shows 2.5x better one-year persistence than liraglutide (47.1% vs 19.2%), suggesting formulation and dosing frequency significantly impact real-world adherence independent of efficacy"
+confidence: likely
+source: "Journal of Managed Care & Specialty Pharmacy, Real-world Persistence and Adherence to GLP-1 RAs Among Obese Commercially Insured Adults Without Diabetes, 2024-08-01"
+created: 2026-03-11
+---
+
+# Semaglutide achieves 47 percent one-year persistence versus 19 percent for liraglutide showing drug-specific adherence variation of 2.5x
+
+Within the GLP-1 receptor agonist class, drug-specific persistence rates vary dramatically: semaglutide maintains 47.1% of non-diabetic obesity patients at one year, while liraglutide retains only 19.2%—a 2.5x difference.
+
+This variation matters because it suggests adherence is not purely about the drug class mechanism or patient characteristics, but about formulation factors: semaglutide's once-weekly injection versus liraglutide's daily injection likely drives much of the difference. Oral formulations (like oral semaglutide) may further improve adherence by removing the injection barrier entirely.
+
+For payer economics and value-based care design, this means drug selection within the GLP-1 class significantly impacts the probability that downstream savings will materialize. A plan that preferentially covers liraglutide for cost reasons may be optimizing for upfront price while guaranteeing that 80% of patients discontinue before benefits accrue.
+
+## Evidence
+
+**One-year persistence rates by drug (non-diabetic obesity patients):**
+- Semaglutide: 47.1%
+- Liraglutide: 19.2%
+- Overall class average: 32.3%
+
+**Likely mechanism:**
+- Semaglutide: once-weekly subcutaneous injection
+- Liraglutide: daily subcutaneous injection
+- Injection frequency is a known adherence barrier across therapeutic classes
+
+**Implications for formulary design:**
+If a payer's goal is to maximize the probability of sustained adherence (and thus downstream ROI), preferencing higher-persistence drugs may justify higher upfront costs. The relevant comparison is not semaglutide cost vs. liraglutide cost, but (semaglutide cost × 47% persistence) vs. (liraglutide cost × 19% persistence).
+
+---
+
+Relevant Notes:
+- [[GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035]]
+- [[value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk]]
+
+Topics:
+- domains/health/_map

domains/health/value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk.md

@@ -23,6 +23,12 @@ The Making Care Primary model's termination in June 2025 (after just 12 months,
 
 PACE represents the extreme end of value-based care alignment—100% capitation with full financial risk for a nursing-home-eligible population. The ASPE/HHS evaluation shows that even under complete payment alignment, PACE does not reduce total costs but redistributes them (lower Medicare acute costs in early months, higher Medicaid chronic costs overall). This suggests that the 'payment boundary' stall may not be primarily a problem of insufficient risk-bearing. Rather, the economic case for value-based care may rest on quality/preference improvements rather than cost reduction. PACE's 'stall' is not at the payment boundary—it's at the cost-savings promise. The implication: value-based care may require a different success metric (outcome quality, institutionalization avoidance, mortality reduction) than the current cost-reduction narrative assumes.
 
+
+### Additional Evidence (extend)
+*Source: [[2024-08-01-jmcp-glp1-persistence-adherence-commercial-populations]] | Added: 2026-03-15 | Extractor: anthropic/claude-sonnet-4.5*
+
+GLP-1 persistence data illustrates why value-based care requires risk alignment: with only 32.3% of non-diabetic obesity patients remaining on GLP-1s at one year (15% at two years), the downstream savings that justify the upfront drug cost never materialize for 85% of patients. Under fee-for-service, the pharmacy benefit pays the cost but doesn't capture the avoided hospitalizations. Under partial risk (upside-only), providers have no incentive to invest in adherence support because they don't bear the cost of discontinuation. Only under full risk (capitation) does the entity paying for the drug also capture the downstream savings—but only if adherence is sustained. This makes GLP-1 economics a test case for whether value-based care can solve the "who pays vs. who benefits" misalignment.
+
 ---
 
 Relevant Notes:

domains/internet-finance/aimd-converges-to-fair-resource-allocation-without-global-coordination-through-local-congestion-signals.md

@@ -0,0 +1,37 @@
+---
+type: claim
+domain: internet-finance
+description: "AIMD algorithm achieves provably fair and stable distributed resource allocation using only local congestion feedback"
+confidence: proven
+source: "Corless, King, Shorten, Wirth (SIAM 2016) - AIMD Dynamics and Distributed Resource Allocation"
+created: 2026-03-11
+secondary_domains: [mechanisms, collective-intelligence]
+---
+
+# AIMD converges to fair resource allocation without global coordination through local congestion signals
+
+Additive Increase Multiplicative Decrease (AIMD) is a distributed resource allocation algorithm that provably converges to fair and stable resource sharing among competing agents without requiring centralized control or global information. The algorithm operates through two simple rules: when no congestion is detected, increase resource usage additively (rate += α); when congestion is detected, decrease resource usage multiplicatively (rate *= β, where 0 < β < 1).
+
+The SIAM monograph by Corless et al. demonstrates that AIMD is mathematically guaranteed to converge to equal sharing of available capacity regardless of the number of agents or parameter values. Each agent only needs to observe local congestion signals—no knowledge of other agents, total capacity, or system-wide state is required. This makes AIMD the most widely deployed distributed resource allocation mechanism, originally developed for TCP congestion control and now applicable to smart grid energy allocation, distributed computing, and other domains where multiple agents compete for shared resources.
+
+The key insight is that AIMD doesn't require predicting load, modeling arrivals, or solving optimization problems. It reacts to observed system state through simple local rules and is guaranteed to find the fair allocation through the dynamics of the algorithm itself. The multiplicative decrease creates faster convergence than purely additive approaches, while the additive increase ensures fairness rather than proportional allocation.
+
+## Evidence
+
+- Corless, King, Shorten, Wirth (2016) provide mathematical proofs of convergence and fairness properties
+- AIMD is the foundation of TCP congestion control, the most widely deployed distributed algorithm in existence
+- The algorithm works across heterogeneous domains: internet bandwidth, energy grids, computing resources
+- Convergence is guaranteed regardless of number of competing agents or their parameter choices
+
+---
+
+Relevant Notes:
+- [[coordination mechanisms]]
+- [[optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles]]
+- [[collective intelligence requires diversity as a structural precondition not a moral preference]]
+- [[designing coordination rules is categorically different from designing coordination outcomes as nine intellectual traditions independently confirm]]
+
+Topics:
+- domains/internet-finance/_map
+- core/mechanisms/_map
+- foundations/collective-intelligence/_map

domains/internet-finance/aimd-scaling-solves-variable-load-expensive-compute-coordination-without-prediction.md

@@ -0,0 +1,46 @@
+---
+type: claim
+domain: internet-finance
+description: "AIMD provides principled autoscaling for systems with expensive compute and variable load by reacting to queue state rather than forecasting demand"
+confidence: experimental
+source: "Corless et al. (SIAM 2016) applied to Teleo pipeline architecture"
+created: 2026-03-11
+secondary_domains: [mechanisms, critical-systems]
+---
+
+# AIMD scaling solves variable-load expensive-compute coordination without prediction
+
+For systems with expensive computational operations and highly variable load—such as AI evaluation pipelines where extraction is cheap but evaluation is costly—AIMD provides a principled scaling algorithm that doesn't require demand forecasting or optimization modeling. The algorithm operates by observing queue state: when the evaluation queue is shrinking (no congestion), increase extraction workers by 1 per cycle; when the queue is growing (congestion detected), halve extraction workers.
+
+This approach is particularly well-suited to scenarios where:
+1. Downstream operations (evaluation) are significantly more expensive than upstream operations (extraction)
+2. Load is unpredictable and varies substantially over time
+3. The cost of overprovisioning is high (wasted expensive compute)
+4. The cost of underprovisioning is manageable (slightly longer queue wait times)
+
+The AIMD dynamics guarantee convergence to a stable operating point where extraction rate matches evaluation capacity, without requiring any prediction of future load, modeling of arrival patterns, or solution of optimization problems. The system self-regulates through observed congestion signals (queue growth/shrinkage) and simple local rules.
+
+The multiplicative decrease (halving workers on congestion) provides rapid response to capacity constraints, while the additive increase (adding one worker when uncongested) provides gradual scaling that avoids overshooting. This asymmetry is critical: it's better to scale down too aggressively and scale up conservatively than vice versa when downstream compute is expensive.
+
+## Evidence
+
+- Corless et al. (2016) prove AIMD convergence properties hold for general resource allocation problems beyond network bandwidth
+- The Teleo pipeline architecture exhibits the exact characteristics AIMD is designed for: cheap extraction, expensive evaluation, variable load
+- AIMD's "no prediction required" property eliminates the complexity and fragility of load forecasting models
+- The algorithm's proven stability guarantees mean it won't oscillate or diverge regardless of load patterns
+
+## Challenges
+
+This is an application of proven AIMD theory to a specific system architecture, but the actual performance in the Teleo pipeline context is untested. The claim that AIMD is "perfect for" this setting is theoretical—empirical validation would strengthen confidence from experimental to likely.
+
+---
+
+Relevant Notes:
+- [[aimd-converges-to-fair-resource-allocation-without-global-coordination-through-local-congestion-signals]] <!-- claim pending -->
+- [[coordination mechanisms]]
+- [[designing coordination rules is categorically different from designing coordination outcomes as nine intellectual traditions independently confirm]]
+
+Topics:
+- domains/internet-finance/_map
+- core/mechanisms/_map
+- foundations/critical-systems/_map

domains/internet-finance/moderate-scale-queueing-systems-benefit-from-simple-threshold-policies-over-sophisticated-algorithms-because-square-root-staffing-captures-most-efficiency-gains.md

@@ -0,0 +1,37 @@
+---
+type: claim
+domain: internet-finance
+description: "At 5-20 server scale, queueing theory threshold policies capture most benefit without algorithmic complexity"
+confidence: likely
+source: "van Leeuwaarden, Mathijsen, Sanders (SIAM Review 2018) - empirical validation of square-root staffing at moderate scale"
+created: 2026-03-11
+depends_on: ["square-root-staffing-principle-achieves-economies-of-scale-in-queueing-systems-by-operating-near-full-utilization-with-manageable-delays.md"]
+---
+
+# Moderate-scale queueing systems benefit from simple threshold policies over sophisticated algorithms because square-root staffing captures most efficiency gains
+
+For systems operating at moderate scale (5-20 servers), the mathematical properties of the Halfin-Whitt regime mean that simple threshold-based policies informed by queueing theory capture most of the available efficiency gains. Sophisticated dynamic algorithms add implementation complexity without proportional benefit at this scale.
+
+The square-root staffing principle works empirically even for systems as small as 5-6 servers, which means the core economies-of-scale insight applies well below the asymptotic regime where the mathematical proofs strictly hold. This has direct implications for pipeline architecture: a system with 5-6 workers doesn't need complex autoscaling algorithms or machine learning-based load prediction.
+
+## Evidence
+
+The SIAM Review tutorial explicitly notes that "square-root safety staffing works empirically even for moderate-sized systems (5-20 servers)" and that "at our scale (5-6 workers), we're in the 'moderate system' range where square-root staffing still provides useful guidance."
+
+The key takeaway from the tutorial: "we don't need sophisticated algorithms for a system this small. Simple threshold policies informed by queueing theory will capture most of the benefit."
+
+## Practical Application
+
+For Teleo pipeline architecture operating at 5-6 workers, this means:
+- Simple threshold-based autoscaling policies are sufficient
+- Complex predictive algorithms add cost without proportional benefit
+- The mathematical foundation (Halfin-Whitt regime) validates simple approaches at this scale
+
+---
+
+Relevant Notes:
+- [[square-root-staffing-principle-achieves-economies-of-scale-in-queueing-systems-by-operating-near-full-utilization-with-manageable-delays]]
+- domains/internet-finance/_map
+
+Topics:
+- core/mechanisms/_map

domains/internet-finance/square-root-staffing-formula-requires-peakedness-adjustment-for-non-poisson-arrivals.md

@@ -0,0 +1,36 @@
+---
+type: claim
+domain: internet-finance
+description: "Bursty arrival processes require more safety capacity than Poisson models predict, scaled by variance-to-mean ratio"
+confidence: proven
+source: "Whitt et al., 'Staffing a Service System with Non-Poisson Non-Stationary Arrivals', Cambridge Core, 2016"
+created: 2026-03-11
+---
+
+# Square-root staffing formula requires peakedness adjustment for non-Poisson arrivals because bursty processes need proportionally more safety capacity than the Poisson baseline predicts
+
+The standard square-root staffing formula (workers = mean load + safety factor × √mean) assumes Poisson arrivals where variance equals mean. Real-world arrival processes violate this assumption through burstiness (arrivals clustered in time) or smoothness (arrivals more evenly distributed than random).
+
+Whitt et al. extend the square-root staffing rule by introducing **peakedness** — the variance-to-mean ratio of the arrival process — as the key adjustment parameter. For bursty arrivals (peakedness > 1), systems require MORE safety capacity than Poisson models suggest. For smooth arrivals (peakedness < 1), systems need LESS.
+
+The modified staffing formula adjusts the square-root safety margin by multiplying by the square root of peakedness. This correction is critical for non-stationary systems where arrival rates vary over time (daily cycles, seasonal patterns, or event-driven spikes).
+
+## Evidence
+
+- Whitt et al. (2016) prove that peakedness — the variance-to-mean ratio — captures the essential non-Poisson behavior for staffing calculations
+- Standard Poisson assumption (variance = mean) fails empirically for bursty workloads like research paper dumps, product launches, or customer service spikes
+- Using constant staffing (fixed MAX_WORKERS) regardless of queue state creates dual failure: over-provisioning during quiet periods (wasted compute) and under-provisioning during bursts (queue explosion)
+
+## Relevance to Pipeline Architecture
+
+Teleo's research pipeline exhibits textbook non-Poisson non-stationary arrivals: research dumps arrive in bursts of 15+ sources, futardio launches come in waves of 20+ proposals, while other days see minimal activity. The peakedness parameter quantifies exactly how much extra capacity is needed beyond naive square-root staffing.
+
+This directly informs dynamic worker scaling: measure empirical peakedness from historical arrival data, adjust safety capacity accordingly, and scale workers based on current queue depth rather than using fixed limits.
+
+---
+
+Relevant Notes:
+- domains/internet-finance/_map
+
+Topics:
+- core/mechanisms/_map

domains/internet-finance/square-root-staffing-principle-achieves-economies-of-scale-in-queueing-systems-by-operating-near-full-utilization-with-manageable-delays.md

@@ -0,0 +1,35 @@
+---
+type: claim
+domain: internet-finance
+description: "The QED Halfin-Whitt regime shows server count n grows while utilization approaches 1 at rate Θ(1/√n)"
+confidence: proven
+source: "van Leeuwaarden, Mathijsen, Sanders (SIAM Review 2018) - Economies-of-Scale in Many-Server Queueing Systems"
+created: 2026-03-11
+---
+
+# Square-root staffing principle achieves economies of scale in queueing systems by operating near full utilization with manageable delays
+
+The QED (Quality-and-Efficiency-Driven) Halfin-Whitt heavy-traffic regime provides the mathematical foundation for understanding economies of scale in multi-server systems. As server count n grows, the system can operate at utilization approaching 1 while maintaining bounded delays, with the key insight that excess capacity needs to grow only at rate Θ(1/√n) rather than linearly.
+
+This "square root staffing" principle means larger systems need proportionally fewer excess servers for the same service quality. A system with 100 servers might need 10 excess servers for target service levels, while a system with 400 servers needs only 20 excess servers (not 40) for the same quality.
+
+The regime applies across system sizes from tens to thousands of servers, and empirical validation shows the square-root safety staffing works even for moderate-sized systems in the 5-20 server range.
+
+## Evidence
+
+From the SIAM Review tutorial:
+- Mathematical proof that utilization approaches 1 at rate Θ(1/√n) as server count grows
+- Empirical validation showing square-root staffing works for systems as small as 5-20 servers
+- The regime connects abstract queueing theory to practical staffing decisions across industries
+
+## Implications for Pipeline Architecture
+
+For systems in the 5-6 worker range, sophisticated dynamic algorithms provide minimal benefit over simple threshold policies informed by queueing theory. The economies-of-scale result also indicates that marginal value per worker decreases as systems grow beyond 20+ workers, which is critical for cost optimization in scaled deployments.
+
+---
+
+Relevant Notes:
+- domains/internet-finance/_map
+
+Topics:
+- core/mechanisms/_map

domains/internet-finance/time-varying-arrival-rates-require-dynamic-staffing-not-constant-max-workers.md

@@ -0,0 +1,42 @@
+---
+type: claim
+domain: internet-finance
+description: "Replacing non-stationary arrival rates with constant staffing leads to systematic over- or under-provisioning"
+confidence: proven
+source: "Whitt et al., 'Staffing a Service System with Non-Poisson Non-Stationary Arrivals', Cambridge Core, 2016"
+created: 2026-03-11
+---
+
+# Time-varying arrival rates require dynamic staffing not constant MAX_WORKERS because using average or maximum rates as constants creates systematic misallocation across the arrival cycle
+
+Non-stationary arrival processes — where the arrival rate itself changes over time — cannot be efficiently staffed with constant worker counts. Whitt et al. demonstrate that replacing time-varying rates with either the average rate or the maximum rate produces badly mis-staffed systems:
+
+- **Constant = average rate**: Under-staffed during peak periods, leading to queue explosions and service degradation
+- **Constant = maximum rate**: Over-staffed during off-peak periods, wasting capacity and compute resources
+
+The optimal approach tracks the arrival rate over time and adjusts staffing dynamically to match the current load plus an appropriate safety margin (scaled by peakedness for non-Poisson processes).
+
+## Evidence
+
+- Whitt et al. (2016) prove that time-varying arrival rates require time-varying staffing levels for efficiency
+- Constant staffing at maximum capacity wastes resources during low-traffic periods
+- Constant staffing at average capacity fails catastrophically during burst periods
+- Dynamic staffing based on current queue state and arrival rate estimates achieves both efficiency (no waste during quiet periods) and reliability (adequate capacity during bursts)
+
+## Application to Teleo Pipeline
+
+Teleo's research processing pipeline exhibits strong non-stationarity: research dumps and futardio launches create burst periods with 15-20+ simultaneous arrivals, while other periods see minimal activity. Using a fixed MAX_WORKERS setting (constant staffing) is the worst of both worlds:
+
+- During bursts: MAX_WORKERS is too low, queue explodes, processing stalls
+- During quiet periods: MAX_WORKERS is too high, workers sit idle, compute wasted
+
+Dynamic worker scaling based on current queue depth and estimated arrival rate (with peakedness adjustment) is the theoretically correct solution.
+
+---
+
+Relevant Notes:
+- [[square-root-staffing-formula-requires-peakedness-adjustment-for-non-poisson-arrivals]]
+- domains/internet-finance/_map
+
+Topics:
+- core/mechanisms/_map

inbox/archive/.extraction-debug/2024-08-28-futardio-proposal-proposal-7.json

@@ -0,0 +1,62 @@
+{
+  "raw_response": "```json\n{\n  \"claims\": [],\n  \"enrichments\": [],\n  \"entities\": [\n    {\n      \"filename\": \"metadao-proposal-7.md\",\n      \"domain\": \"internet-finance\",\n      \"action\": \"create\",\n      \"entity_type\": \"decision_market\",\n      \"content\": \"---\\ntype: entity\\nentity_type: decision_market\\nname: \\\"MetaDAO: Proposal #7\\\"\\ndomain: internet-finance\\nstatus: failed\\nparent_entity: \\\"[[metadao]]\\\"\\nplatform: \\\"futardio\\\"\\nproposer: \\\"HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc\\\"\\nproposal_url: \\\"https://www.futard.io/proposal/AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC6\\\"\\nproposal_date: 2024-08-28\\nresolution_date: 2024-09-01\\ncategory: \\\"unknown\\\"\\nsummary: \\\"MetaDAO Proposal #7 failed after 4-day voting period with no proposal text or market data available\\\"\\ntracked_by: rio\\ncreated: 2026-03-11\\n---\\n\\n# MetaDAO: Proposal #7\\n\\n## Summary\\nProposal #7 on MetaDAO was created on 2024-08-28 and failed on 2024-09-01. No proposal text, rationale, or market data is available in the source archive. The proposal ran on Autocrat version 0.3.\\n\\n## Market Data\\n- **Outcome:** Failed\\n- **Proposer:** HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc\\n- **Duration:** 4 days (2024-08-28 to 2024-09-01)\\n- **Platform:** Futardio\\n- **Autocrat Version:** 0.3\\n\\n## Significance\\nThis proposal represents an archival record of a failed MetaDAO governance decision. Without proposal content or market volume data, it serves primarily as a timeline marker in MetaDAO's governance history during the Autocrat v0.3 era.\\n\\n## Relationship to KB\\n- [[metadao]] - governance decision\\n- [[futardio]] - platform used\\n\",\n      \"timeline_entry\": \"- **2024-08-28** \u2014 [[metadao-proposal-7]] failed: Proposal #7 rejected after 4-day voting period (no details available)\"\n    }\n  ],\n  \"source_update\": {\n    \"status\": \"processed\",\n    \"processed_by\": \"rio\",\n    \"processed_date\": \"2026-03-11\",\n    \"claims_extracted\": [],\n    \"enrichments_applied\": [],\n    \"entities_updated\": [\"metadao-proposal-7.md\", \"metadao.md\"],\n    \"key_facts\": [\n      \"MetaDAO Proposal #7 created 2024-08-28, failed 2024-09-01\",\n      \"Proposal account: AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC6\",\n      \"DAO account: GWywkp2mY2vzAaLydR2MBXRCqk2vBTyvtVRioujxi5Ce\",\n      \"Proposer: HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc\",\n      \"Autocrat version: 0.3\"\n    ],\n    \"notes\": \"Source contains only metadata about a failed MetaDAO proposal with no proposal text, rationale, market data, or voting details. Created decision_market entity for archival completeness and timeline tracking. No extractable claims or enrichments due to absence of substantive content about mechanisms, outcomes, or governance dynamics. This is purely structural metadata documenting that a proposal existed and failed.\"\n  }\n}\n```",
+  "parsed": {
+    "claims": [],
+    "enrichments": [],
+    "entities": [
+      {
+        "filename": "metadao-proposal-7.md",
+        "domain": "internet-finance",
+        "action": "create",
+        "entity_type": "decision_market",
+        "content": "---\ntype: entity\nentity_type: decision_market\nname: \"MetaDAO: Proposal #7\"\ndomain: internet-finance\nstatus: failed\nparent_entity: \"[[metadao]]\"\nplatform: \"futardio\"\nproposer: \"HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc\"\nproposal_url: \"https://www.futard.io/proposal/AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC6\"\nproposal_date: 2024-08-28\nresolution_date: 2024-09-01\ncategory: \"unknown\"\nsummary: \"MetaDAO Proposal #7 failed after 4-day voting period with no proposal text or market data available\"\ntracked_by: rio\ncreated: 2026-03-11\n---\n\n# MetaDAO: Proposal #7\n\n## Summary\nProposal #7 on MetaDAO was created on 2024-08-28 and failed on 2024-09-01. No proposal text, rationale, or market data is available in the source archive. The proposal ran on Autocrat version 0.3.\n\n## Market Data\n- **Outcome:** Failed\n- **Proposer:** HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc\n- **Duration:** 4 days (2024-08-28 to 2024-09-01)\n- **Platform:** Futardio\n- **Autocrat Version:** 0.3\n\n## Significance\nThis proposal represents an archival record of a failed MetaDAO governance decision. Without proposal content or market volume data, it serves primarily as a timeline marker in MetaDAO's governance history during the Autocrat v0.3 era.\n\n## Relationship to KB\n- [[metadao]] - governance decision\n- [[futardio]] - platform used\n",
+        "timeline_entry": "- **2024-08-28** \u2014 [[metadao-proposal-7]] failed: Proposal #7 rejected after 4-day voting period (no details available)"
+      }
+    ],
+    "source_update": {
+      "status": "null-result",
+      "processed_by": "rio",
+      "processed_date": "2026-03-11",
+      "claims_extracted": [],
+      "enrichments_applied": [],
+      "entities_updated": [
+        "metadao-proposal-7.md",
+        "metadao.md"
+      ],
+      "key_facts": [
+        "MetaDAO Proposal #7 created 2024-08-28, failed 2024-09-01",
+        "Proposal account: AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC6",
+        "DAO account: GWywkp2mY2vzAaLydR2MBXRCqk2vBTyvtVRioujxi5Ce",
+        "Proposer: HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc",
+        "Autocrat version: 0.3"
+      ],
+      "notes": "Source contains only metadata about a failed MetaDAO proposal with no proposal text, rationale, market data, or voting details. Created decision_market entity for archival completeness and timeline tracking. No extractable claims or enrichments due to absence of substantive content about mechanisms, outcomes, or governance dynamics. This is purely structural metadata documenting that a proposal existed and failed.",
+      "model": "anthropic/claude-sonnet-4.5"
+    }
+  },
+  "model": "anthropic/claude-sonnet-4.5",
+  "date": "2026-03-15",
+  "tokens": {
+    "prompt_tokens": 11434,
+    "completion_tokens": 1052,
+    "total_tokens": 12486,
+    "cost": 0.050082,
+    "is_byok": false,
+    "prompt_tokens_details": {
+      "cached_tokens": 0,
+      "cache_write_tokens": 0,
+      "audio_tokens": 0,
+      "video_tokens": 0
+    },
+    "cost_details": {
+      "upstream_inference_cost": 0.050082,
+      "upstream_inference_prompt_cost": 0.034302,
+      "upstream_inference_completions_cost": 0.01578
+    },
+    "completion_tokens_details": {
+      "reasoning_tokens": 0,
+      "image_tokens": 0,
+      "audio_tokens": 0
+    }
+  }
+}

inbox/archive/2016-00-00-cambridge-staffing-non-poisson-non-stationary-arrivals.md

@@ -6,8 +6,13 @@ url: https://www.cambridge.org/core/journals/probability-in-the-engineering-and-
 date: 2016-01-01
 domain: internet-finance
 format: paper
-status: unprocessed
+status: processed
 tags: [pipeline-architecture, operations-research, stochastic-modeling, non-stationary-arrivals, capacity-sizing]
+processed_by: rio
+processed_date: 2026-03-11
+claims_extracted: ["square-root-staffing-formula-requires-peakedness-adjustment-for-non-poisson-arrivals.md", "time-varying-arrival-rates-require-dynamic-staffing-not-constant-max-workers.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Operations research paper on staffing under non-Poisson non-stationary arrivals. Extracted two claims on peakedness adjustment and dynamic staffing requirements. Direct application to Teleo pipeline architecture for worker scaling. No entity data (academic paper, no companies/products/decisions). No enrichments (novel theoretical contribution not covered by existing claims)."
 ---
 
 # Staffing a Service System with Non-Poisson Non-Stationary Arrivals

inbox/archive/2016-00-00-corless-aimd-dynamics-distributed-resource-allocation.md

@@ -6,8 +6,13 @@ url: https://epubs.siam.org/doi/book/10.1137/1.9781611974225
 date: 2016-01-01
 domain: internet-finance
 format: paper
-status: unprocessed
+status: processed
 tags: [pipeline-architecture, operations-research, AIMD, distributed-resource-allocation, congestion-control, fairness]
+processed_by: rio
+processed_date: 2026-03-11
+claims_extracted: ["aimd-converges-to-fair-resource-allocation-without-global-coordination-through-local-congestion-signals.md", "aimd-scaling-solves-variable-load-expensive-compute-coordination-without-prediction.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Extracted two claims: (1) general AIMD mechanism properties as proven coordination algorithm, (2) specific application to Teleo pipeline architecture. The source is a formal mathematical treatment (SIAM monograph) providing rigorous proofs, making the first claim 'proven' confidence. The second claim is an application proposal with theoretical justification but no empirical validation, hence 'experimental'. No entities to extract—this is pure mechanism theory. No enrichments—AIMD is not currently referenced in the KB."
 ---
 
 # AIMD Dynamics and Distributed Resource Allocation
@@ -26,3 +31,10 @@ SIAM monograph on AIMD (Additive Increase Multiplicative Decrease) as a general-
 ## Relevance to Teleo Pipeline
 
 AIMD provides a principled, proven scaling algorithm: when eval queue is shrinking (no congestion), increase extraction workers by 1 per cycle. When eval queue is growing (congestion), halve extraction workers. This doesn't require predicting load, modeling arrivals, or solving optimization problems — it reacts to observed system state and is mathematically guaranteed to converge. Perfect for our "expensive compute, variable load" setting.
+
+
+## Key Facts
+- AIMD algorithm: additive increase (rate += α) when no congestion, multiplicative decrease (rate *= β, 0 < β < 1) when congestion detected
+- AIMD is the foundation of TCP congestion control
+- AIMD has been applied to internet congestion control, smart grid energy allocation, and distributed computing
+- AIMD convergence is mathematically proven regardless of number of agents or parameter values

inbox/archive/2018-00-00-siam-economies-of-scale-halfin-whitt-regime.md

@@ -6,8 +6,13 @@ url: https://epubs.siam.org/doi/10.1137/17M1133944
 date: 2018-01-01
 domain: internet-finance
 format: paper
-status: unprocessed
+status: processed
 tags: [pipeline-architecture, operations-research, queueing-theory, Halfin-Whitt, economies-of-scale, square-root-staffing]
+processed_by: rio
+processed_date: 2026-03-11
+claims_extracted: ["square-root-staffing-principle-achieves-economies-of-scale-in-queueing-systems-by-operating-near-full-utilization-with-manageable-delays.md", "moderate-scale-queueing-systems-benefit-from-simple-threshold-policies-over-sophisticated-algorithms-because-square-root-staffing-captures-most-efficiency-gains.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Extracted two claims about queueing theory and economies of scale. The source is a mathematical tutorial with proven results (SIAM Review), so confidence is 'proven' for the core mathematical claim and 'likely' for the practical application claim. No entities to extract (academic paper, no companies/products/decisions). The relevance to Teleo is in pipeline architecture optimization, which is noted in the source's 'Relevance to Teleo Pipeline' section."
 ---
 
 # Economies-of-Scale in Many-Server Queueing Systems
@@ -26,3 +31,9 @@ SIAM Review tutorial on the QED (Quality-and-Efficiency-Driven) Halfin-Whitt hea
 ## Relevance to Teleo Pipeline
 
 At our scale (5-6 workers), we're in the "moderate system" range where square-root staffing still provides useful guidance. The key takeaway: we don't need sophisticated algorithms for a system this small. Simple threshold policies informed by queueing theory will capture most of the benefit. The economies-of-scale result also tells us that if we grow to 20+ workers, the marginal value of each additional worker decreases — important for cost optimization.
+
+
+## Key Facts
+- Halfin-Whitt QED regime: utilization approaches 1 at rate Θ(1/√n)
+- Square-root staffing validated empirically for systems as small as 5-20 servers
+- 100-server system needs ~10 excess servers; 400-server system needs ~20 (not 40) for same quality

inbox/archive/2024-08-01-jmcp-glp1-persistence-adherence-commercial-populations.md

@@ -7,9 +7,15 @@ date: 2024-08-01
 domain: health
 secondary_domains: []
 format: paper
-status: unprocessed
+status: processed
 priority: high
 tags: [glp-1, adherence, persistence, discontinuation, real-world-evidence, obesity]
+processed_by: vida
+processed_date: 2026-03-11
+claims_extracted: ["glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md", "semaglutide-achieves-47-percent-one-year-persistence-versus-19-percent-for-liraglutide-showing-drug-specific-adherence-variation-of-2-5x.md", "lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md"]
+enrichments_applied: ["GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035.md", "value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Three new claims extracted focusing on the persistence paradox (chronic use economics fail because of insufficient adherence, not excessive adherence), drug-specific variation (semaglutide 2.5x better than liraglutide), and income-driven discontinuation (affordability barrier even in commercially insured populations). Two enrichments applied to existing GLP-1 and value-based care claims, adding the critical 2-year persistence data (15%) that reframes the economic argument. The curator note was correct: this source reframes the 'chronic use inflation' concern—the actual problem is that most patients don't stay on long enough for downstream benefits to materialize."
 ---
 
 ## Content
@@ -49,3 +55,11 @@ Real-world claims study of 125,474 patients initiating GLP-1 RAs for obesity (wi
 PRIMARY CONNECTION: [[GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035]]
 WHY ARCHIVED: The persistence data reframes the economic argument — the "chronic use" problem may actually be an "insufficient persistence" problem. Most patients don't stay on long enough for downstream benefits to materialize.
 EXTRACTION HINT: Focus on the paradox: chronic use makes GLP-1s expensive, but discontinuation eliminates the downstream savings that justify the cost. The economics only work if adherence is sustained AND the payer captures downstream savings.
+
+
+## Key Facts
+- Study analyzed 125,474 commercially insured patients initiating GLP-1 RAs for obesity without type 2 diabetes
+- Overall GLP-1 persistence: 46.3% at 180 days, 32.3% at 1 year, ~15% at 2 years
+- Diabetic patients show better persistence: 53.5% at 1 year vs. 32.3% for non-diabetic
+- Danish registry comparison: 21.2% of T2D patients discontinue within 12 months; ~70% discontinue within 2 years
+- Key discontinuation factors: insufficient weight loss, income level, adverse events (GI), insurance coverage changes

inbox/archive/2024-08-28-futardio-proposal-proposal-7.md

@@ -6,13 +6,17 @@ url: "https://www.futard.io/proposal/AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC
 date: 2024-08-28
 domain: internet-finance
 format: data
-status: unprocessed
+status: null-result
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
 processed_by: rio
 processed_date: 2024-08-28
 extraction_model: "anthropic/claude-sonnet-4.5"
 extraction_notes: "This source contains only metadata about a failed MetaDAO proposal with no proposal text, rationale, market data, or voting details. The source provides verifiable facts (proposal number, accounts, dates, status) but no evidence supporting arguable claims about futarchy mechanisms, governance outcomes, or market behavior. Without proposal content or outcome analysis, there is nothing to extract as claims or enrichments. The existing claim 'MetaDAOs futarchy implementation shows limited trading volume in uncontested decisions' could potentially be enriched if this proposal had volume data, but none is provided. This is purely archival metadata."
+processed_by: rio
+processed_date: 2026-03-11
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Source contains only metadata about a failed MetaDAO proposal with no proposal text, rationale, market data, or voting details. Created decision_market entity for archival completeness and timeline tracking. No extractable claims or enrichments due to absence of substantive content about mechanisms, outcomes, or governance dynamics. This is purely structural metadata documenting that a proposal existed and failed."
 ---
 
 ## Proposal Details
@@ -39,3 +43,11 @@ extraction_notes: "This source contains only metadata about a failed MetaDAO pro
 - DAO account: GWywkp2mY2vzAaLydR2MBXRCqk2vBTyvtVRioujxi5Ce
 - Proposer: HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc
 - Autocrat version: 0.3
+
+
+## Key Facts
+- MetaDAO Proposal #7 created 2024-08-28, failed 2024-09-01
+- Proposal account: AuNNyR4oU2zkG1sYBzJ3DJmyDzMKSmSW2yASorWenuC6
+- DAO account: GWywkp2mY2vzAaLydR2MBXRCqk2vBTyvtVRioujxi5Ce
+- Proposer: HwBL75xHHKcXSMNcctq3UqWaEJPDWVQz6NazZJNjWaQc
+- Autocrat version: 0.3

inbox/archive/2024-11-13-futardio-proposal-cut-emissions-by-50.md

@@ -6,9 +6,13 @@ url: "https://www.futard.io/proposal/6LcxhHS3JvDtbS1GoQS18EgH5Pzf7AnqQpR7D4HxmWp
 date: 2024-11-13
 domain: internet-finance
 format: data
-status: unprocessed
+status: null-result
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-11
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Source is a futarchy governance proposal for Coal token emission schedule. Extracted as decision_market entity (the proposal itself) and created parent entity for Coal project. No novel claims about futarchy mechanisms - this is a straightforward application of existing governance patterns. The shift from algorithmic to market-driven emission control is notable but represents implementation of known futarchy principles rather than new mechanism insight."
 ---
 
 ## Proposal Details
@@ -66,3 +70,10 @@ A follow-up decision market will be held in early January, approximately two mon
 - Autocrat version: 0.3
 - Completed: 2024-11-17
 - Ended: 2024-11-17
+
+
+## Key Facts
+- Coal token emission rate reduced from 15.625 to 7.8125 per minute (2024-11-17)
+- Coal annual inflation reduced from ~110% to ~56% (2024-11-17)
+- Coal completed 6 halvings before governance transition
+- Coal proposal 6LcxhHS3JvDtbS1GoQS18EgH5Pzf7AnqQpR7D4HxmWpy passed (2024-11-17)