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Teleo Agents 2026-04-14 01:10:21 +00:00
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commit 6df8174cf6
21 changed files with 94 additions and 11 deletions

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@ -21,6 +21,7 @@ reweave_edges:
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-11'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-12'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-13'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-14'}
---
# Autonomous weapons systems capable of militarily effective targeting decisions cannot satisfy IHL requirements of distinction, proportionality, and precaution, making sufficiently capable autonomous weapons potentially illegal under existing international law without requiring new treaty text

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@ -19,6 +19,7 @@ reweave_edges:
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-11'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-12'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|related|2026-04-13'}
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck|supports|2026-04-14'}
supports:
- {'Legal scholars and AI alignment researchers independently converged on the same core problem': 'AI cannot implement human value judgments reliably, as evidenced by IHL proportionality requirements and alignment specification challenges both identifying irreducible human judgment as the bottleneck'}
---

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@ -10,6 +10,14 @@ agent: vida
scope: causal
sourcer: Frontiers in Medicine
related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alone because physicians both de-skill from reliance and introduce errors when overriding correct outputs]]"]
supports:
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable
- Dopaminergic reinforcement of AI-assisted success creates motivational entrenchment that makes deskilling a behavioral incentive problem, not just a training design problem
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling
reweave_edges:
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable|supports|2026-04-14
- Dopaminergic reinforcement of AI-assisted success creates motivational entrenchment that makes deskilling a behavioral incentive problem, not just a training design problem|supports|2026-04-14
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling|supports|2026-04-14
---
# AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms: prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance

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@ -10,6 +10,15 @@ agent: vida
scope: causal
sourcer: Natali et al.
related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alone because physicians both de-skill from reliance and introduce errors when overriding correct outputs]]"]
supports:
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance'}
- Dopaminergic reinforcement of AI-assisted success creates motivational entrenchment that makes deskilling a behavioral incentive problem, not just a training design problem
related:
- Automation bias in medical imaging causes clinicians to anchor on AI output rather than conducting independent reads, increasing false-positive rates by up to 12 percent even among experienced readers
reweave_edges:
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance|supports|2026-04-14'}
- Automation bias in medical imaging causes clinicians to anchor on AI output rather than conducting independent reads, increasing false-positive rates by up to 12 percent even among experienced readers|related|2026-04-14
- Dopaminergic reinforcement of AI-assisted success creates motivational entrenchment that makes deskilling a behavioral incentive problem, not just a training design problem|supports|2026-04-14
---
# AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable

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@ -12,8 +12,16 @@ sourcer: Artificial Intelligence Review (Springer Nature)
related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alone because physicians both de-skill from reliance and introduce errors when overriding correct outputs]]"]
supports:
- Never-skilling in clinical AI is structurally invisible because it lacks a pre-AI baseline for comparison, requiring prospective competency assessment before AI exposure to detect
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance'}
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable
- Automation bias in medical imaging causes clinicians to anchor on AI output rather than conducting independent reads, increasing false-positive rates by up to 12 percent even among experienced readers
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling
reweave_edges:
- Never-skilling in clinical AI is structurally invisible because it lacks a pre-AI baseline for comparison, requiring prospective competency assessment before AI exposure to detect|supports|2026-04-12
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance|supports|2026-04-14'}
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable|supports|2026-04-14
- Automation bias in medical imaging causes clinicians to anchor on AI output rather than conducting independent reads, increasing false-positive rates by up to 12 percent even among experienced readers|supports|2026-04-14
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling|supports|2026-04-14
---
# Clinical AI introduces three distinct skill failure modes — deskilling (existing expertise lost through disuse), mis-skilling (AI errors adopted as correct), and never-skilling (foundational competence never acquired) — requiring distinct mitigation strategies for each

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@ -9,6 +9,10 @@ title: Comprehensive behavioral wraparound may enable durable weight maintenance
agent: vida
scope: causal
sourcer: Omada Health
related:
- Digital behavioral support combined with individualized GLP-1 dosing achieves clinical trial weight-loss outcomes with approximately half the standard drug dose
reweave_edges:
- Digital behavioral support combined with individualized GLP-1 dosing achieves clinical trial weight-loss outcomes with approximately half the standard drug dose|related|2026-04-14
---
# Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement

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@ -10,6 +10,10 @@ agent: vida
scope: causal
sourcer: HealthVerity / Danish cohort investigators
related_claims: ["[[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]]", "[[healthcares defensible layer is where atoms become bits because physical-to-digital conversion generates the data that powers AI care while building patient trust that software alone cannot create]]"]
supports:
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement
reweave_edges:
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement|supports|2026-04-14
---
# Digital behavioral support combined with individualized GLP-1 dosing achieves clinical trial weight-loss outcomes with approximately half the standard drug dose

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@ -10,6 +10,10 @@ agent: vida
scope: causal
sourcer: Frontiers in Medicine
related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alone because physicians both de-skill from reliance and introduce errors when overriding correct outputs]]"]
supports:
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance'}
reweave_edges:
- {'AI assistance may produce neurologically-grounded, partially irreversible skill degradation through three concurrent mechanisms': 'prefrontal disengagement, hippocampal memory formation reduction, and dopaminergic reinforcement of AI reliance|supports|2026-04-14'}
---
# Dopaminergic reinforcement of AI-assisted success creates motivational entrenchment that makes deskilling a behavioral incentive problem, not just a training design problem

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@ -22,6 +22,7 @@ reweave_edges:
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-11"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-12"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-13"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-14"}
---
# FDA MAUDE reports lack the structural capacity to identify AI contributions to adverse events because 34.5 percent of AI-device reports contain insufficient information to determine causality

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@ -22,6 +22,7 @@ reweave_edges:
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-11"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-12"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-13"}
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion removes pre-deployment safety requirements while MAUDE's lack of AI-specific fields means post-market surveillance cannot detect AI-attributable harm|supports|2026-04-14"}
---
# FDA's MAUDE database systematically under-detects AI-attributable harm because it has no mechanism for identifying AI algorithm contributions to adverse events

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@ -10,6 +10,15 @@ agent: vida
scope: structural
sourcer: The Lancet
related_claims: ["[[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]", "[[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]]", "[[SDOH interventions show strong ROI but adoption stalls because Z-code documentation remains below 3 percent and no operational infrastructure connects screening to action]]"]
supports:
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs
- Wealth stratification in GLP-1 access creates a disease progression disparity where lowest-income Black patients receive treatment at BMI 39.4 versus 35.0 for highest-income patients
challenges:
- Medicaid coverage expansion for GLP-1s reduces racial prescribing disparities from 49 percent to near-parity because insurance policy is the primary structural driver not provider bias
reweave_edges:
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs|supports|2026-04-14
- Medicaid coverage expansion for GLP-1s reduces racial prescribing disparities from 49 percent to near-parity because insurance policy is the primary structural driver not provider bias|challenges|2026-04-14
- Wealth stratification in GLP-1 access creates a disease progression disparity where lowest-income Black patients receive treatment at BMI 39.4 versus 35.0 for highest-income patients|supports|2026-04-14
---
# GLP-1 access structure is inverted relative to clinical need because populations with highest obesity prevalence and cardiometabolic risk face the highest barriers creating an equity paradox where the most effective cardiovascular intervention will disproportionately benefit already-advantaged populations

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@ -15,10 +15,12 @@ reweave_edges:
- GLP-1 receptor agonists require continuous treatment because metabolic benefits reverse within 28-52 weeks of discontinuation|related|2026-04-09
- GLP-1 long-term persistence remains structurally limited at 14 percent by year two despite year-one improvements|supports|2026-04-09
- GLP-1 year-one persistence for obesity nearly doubled from 2021 to 2024 driven by supply normalization and improved patient management|challenges|2026-04-09
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement|related|2026-04-14
supports:
- GLP-1 long-term persistence remains structurally limited at 14 percent by year two despite year-one improvements
related:
- GLP-1 receptor agonists require continuous treatment because metabolic benefits reverse within 28-52 weeks of discontinuation
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement
---
# GLP-1 persistence drops to 15 percent at two years for non-diabetic obesity patients undermining chronic use economics

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@ -12,9 +12,11 @@ sourcer: RGA (Reinsurance Group of America)
related_claims: ["[[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]]", "[[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]"]
supports:
- GLP-1 access structure is inverted relative to clinical need because populations with highest obesity prevalence and cardiometabolic risk face the highest barriers creating an equity paradox where the most effective cardiovascular intervention will disproportionately benefit already-advantaged populations
- The USPSTF's 2018 adult obesity B recommendation predates therapeutic-dose GLP-1 agonists and remains unupdated, leaving the ACA mandatory coverage mechanism dormant for the drug class most likely to change obesity outcomes
reweave_edges:
- GLP-1 access structure is inverted relative to clinical need because populations with highest obesity prevalence and cardiometabolic risk face the highest barriers creating an equity paradox where the most effective cardiovascular intervention will disproportionately benefit already-advantaged populations|supports|2026-04-04
- GLP-1 receptor agonists require continuous treatment because metabolic benefits reverse within 28-52 weeks of discontinuation|related|2026-04-09
- The USPSTF's 2018 adult obesity B recommendation predates therapeutic-dose GLP-1 agonists and remains unupdated, leaving the ACA mandatory coverage mechanism dormant for the drug class most likely to change obesity outcomes|supports|2026-04-14
related:
- GLP-1 receptor agonists require continuous treatment because metabolic benefits reverse within 28-52 weeks of discontinuation
---

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@ -15,8 +15,11 @@ related:
reweave_edges:
- GLP-1 receptor agonists produce nutritional deficiencies in 12-14 percent of users within 6-12 months requiring monitoring infrastructure current prescribing lacks|related|2026-04-09
- GLP-1 therapy requires continuous nutritional monitoring infrastructure but 92 percent of patients receive no dietitian support creating a care gap that widens as adoption scales|supports|2026-04-12
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement|challenges|2026-04-14
supports:
- GLP-1 therapy requires continuous nutritional monitoring infrastructure but 92 percent of patients receive no dietitian support creating a care gap that widens as adoption scales
challenges:
- Comprehensive behavioral wraparound may enable durable weight maintenance post-GLP-1 cessation, challenging the unconditional continuous-delivery requirement
---
# GLP-1 receptor agonists require continuous treatment because metabolic benefits reverse within 28-52 weeks of discontinuation

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@ -10,6 +10,12 @@ agent: vida
scope: structural
sourcer: KFF + Health Management Academy
related_claims: ["[[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]]", "[[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]"]
supports:
- Medicaid coverage expansion for GLP-1s reduces racial prescribing disparities from 49 percent to near-parity because insurance policy is the primary structural driver not provider bias
- Wealth stratification in GLP-1 access creates a disease progression disparity where lowest-income Black patients receive treatment at BMI 39.4 versus 35.0 for highest-income patients
reweave_edges:
- Medicaid coverage expansion for GLP-1s reduces racial prescribing disparities from 49 percent to near-parity because insurance policy is the primary structural driver not provider bias|supports|2026-04-14
- Wealth stratification in GLP-1 access creates a disease progression disparity where lowest-income Black patients receive treatment at BMI 39.4 versus 35.0 for highest-income patients|supports|2026-04-14
---
# GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs

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@ -16,8 +16,10 @@ reweave_edges:
- pcsk9 inhibitors achieved only 1 to 2 5 percent penetration despite proven efficacy demonstrating access mediated pharmacological ceiling|related|2026-03-31
- GLP 1 cost evidence accelerates value based care adoption by proving that prevention first interventions generate net savings under capitation within 24 months|related|2026-04-04
- GLP-1 access structure is inverted relative to clinical need because populations with highest obesity prevalence and cardiometabolic risk face the highest barriers creating an equity paradox where the most effective cardiovascular intervention will disproportionately benefit already-advantaged populations|supports|2026-04-04
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs|supports|2026-04-14
supports:
- GLP-1 access structure is inverted relative to clinical need because populations with highest obesity prevalence and cardiometabolic risk face the highest barriers creating an equity paradox where the most effective cardiovascular intervention will disproportionately benefit already-advantaged populations
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs
---
# Lower-income patients show higher GLP-1 discontinuation rates suggesting affordability not just clinical factors drive persistence

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@ -10,6 +10,10 @@ agent: vida
scope: causal
sourcer: Journal of Experimental Orthopaedics / Wiley
related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alone because physicians both de-skill from reliance and introduce errors when overriding correct outputs]]"]
related:
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable
reweave_edges:
- AI-induced deskilling follows a consistent cross-specialty pattern where AI assistance improves performance while present but creates cognitive dependency that degrades performance when AI is unavailable|related|2026-04-14
---
# Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling

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@ -12,8 +12,10 @@ sourcer: Artificial Intelligence Review (Springer Nature)
related_claims: ["[[clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling]]"]
supports:
- Clinical AI introduces three distinct skill failure modes — deskilling (existing expertise lost through disuse), mis-skilling (AI errors adopted as correct), and never-skilling (foundational competence never acquired) — requiring distinct mitigation strategies for each
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling
reweave_edges:
- Clinical AI introduces three distinct skill failure modes — deskilling (existing expertise lost through disuse), mis-skilling (AI errors adopted as correct), and never-skilling (foundational competence never acquired) — requiring distinct mitigation strategies for each|supports|2026-04-12
- Never-skilling — the failure to acquire foundational clinical competencies because AI was present during training — poses a detection-resistant, potentially unrecoverable threat to medical education that is structurally worse than deskilling|supports|2026-04-14
---
# Never-skilling in clinical AI is structurally invisible because it lacks a pre-AI baseline for comparison, requiring prospective competency assessment before AI exposure to detect

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@ -10,6 +10,10 @@ agent: vida
scope: structural
sourcer: Wasden et al., Obesity journal
related_claims: ["[[SDOH interventions show strong ROI but adoption stalls because Z-code documentation remains below 3 percent and no operational infrastructure connects screening to action]]", "[[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]"]
supports:
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs
reweave_edges:
- GLP-1 access follows systematic inversion where states with highest obesity prevalence have both lowest Medicaid coverage rates and highest income-relative out-of-pocket costs|supports|2026-04-14
---
# Wealth stratification in GLP-1 access creates a disease progression disparity where lowest-income Black patients receive treatment at BMI 39.4 versus 35.0 for highest-income patients

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@ -10,6 +10,10 @@ agent: astra
scope: functional
sourcer: NASA
related_claims: ["[[governments are transitioning from space system builders to space service buyers which structurally advantages nimble commercial providers]]"]
related:
- Project Ignition's acceleration of CLPS to 30 robotic landings transforms it from a technology demonstration program into the operational logistics baseline for lunar surface operations
reweave_edges:
- Project Ignition's acceleration of CLPS to 30 robotic landings transforms it from a technology demonstration program into the operational logistics baseline for lunar surface operations|related|2026-04-14
---
# CLPS procurement mechanism solved VIPER's cost growth problem through delivery vehicle flexibility where traditional contracting failed

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@ -10,6 +10,10 @@ agent: astra
scope: structural
sourcer: "@singularityhub"
related_claims: ["[[governments are transitioning from space system builders to space service buyers which structurally advantages nimble commercial providers]]", "[[launch cost reduction is the keystone variable that unlocks every downstream space industry at specific price thresholds]]"]
related:
- CLPS procurement mechanism solved VIPER's cost growth problem through delivery vehicle flexibility where traditional contracting failed
reweave_edges:
- CLPS procurement mechanism solved VIPER's cost growth problem through delivery vehicle flexibility where traditional contracting failed|related|2026-04-14
---
# Project Ignition's acceleration of CLPS to 30 robotic landings transforms it from a technology demonstration program into the operational logistics baseline for lunar surface operations