From f0f746e411fd48b2b3ac47109036f504372efc7b Mon Sep 17 00:00:00 2001 From: Teleo Agents Date: Tue, 14 Apr 2026 01:09:42 +0000 Subject: [PATCH] reweave: connect 15 orphan claims via vector similarity Threshold: 0.7, Haiku classification, 21 files modified. Pentagon-Agent: Epimetheus <0144398e-4ed3-4fe2-95a3-3d72e1abf887> --- ...HL-because-proportionality-requires-human-judgment.md | 2 ++ ...-alignment-converge-on-explainability-requirements.md | 2 ++ ...ppocampal-reduction-and-dopaminergic-reinforcement.md | 8 ++++++++ ...ows-consistent-cross-specialty-pattern-in-medicine.md | 9 +++++++++ ...failure-modes-deskilling-misskilling-neverskilling.md | 8 ++++++++ ...les-durable-weight-maintenance-post-glp1-cessation.md | 4 ++++ ...dose-reduction-while-maintaining-clinical-outcomes.md | 4 ++++ ...avioral-entrenchment-beyond-simple-habit-formation.md | 4 ++++ ...to-adverse-events-due-to-structural-reporting-gaps.md | 2 ++ ...systematic-under-detection-of-ai-attributable-harm.md | 2 ++ ...ess-structure-inverts-need-creating-equity-paradox.md | 9 +++++++++ ...obesity-patients-undermining-chronic-use-economics.md | 2 ++ ...layed-20-years-by-access-and-adherence-constraints.md | 2 ++ ...fits-reverse-within-28-52-weeks-of-discontinuation.md | 3 +++ ...e-lowest-coverage-and-highest-income-relative-cost.md | 6 ++++++ ...bility-not-just-clinical-factors-drive-persistence.md | 2 ++ ...-and-unrecoverable-making-it-worse-than-deskilling.md | 4 ++++ ...seline-requiring-prospective-competency-assessment.md | 2 ++ ...me-black-patients-treated-at-13-percent-higher-bmi.md | 4 ++++ ...er-procurement-problem-through-vehicle-flexibility.md | 4 ++++ ...to-lunar-logistics-baseline-under-project-ignition.md | 4 ++++ 21 files changed, 87 insertions(+) diff --git a/domains/ai-alignment/autonomous-weapons-violate-existing-IHL-because-proportionality-requires-human-judgment.md b/domains/ai-alignment/autonomous-weapons-violate-existing-IHL-because-proportionality-requires-human-judgment.md index d4818eefd..6b872855e 100644 --- a/domains/ai-alignment/autonomous-weapons-violate-existing-IHL-because-proportionality-requires-human-judgment.md +++ b/domains/ai-alignment/autonomous-weapons-violate-existing-IHL-because-proportionality-requires-human-judgment.md @@ -13,6 +13,7 @@ related_claims: ["[[AI alignment is a coordination problem not a technical probl 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'} - International humanitarian law and AI alignment research independently converged on the same technical limitation that autonomous systems cannot be adequately predicted understood or explained +- 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 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|2026-04-06'} - International humanitarian law and AI alignment research independently converged on the same technical limitation that autonomous systems cannot be adequately predicted understood or explained|supports|2026-04-08 @@ -21,6 +22,7 @@ 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 diff --git a/domains/ai-alignment/international-humanitarian-law-and-ai-alignment-converge-on-explainability-requirements.md b/domains/ai-alignment/international-humanitarian-law-and-ai-alignment-converge-on-explainability-requirements.md index 5bd297136..c41f5c5c8 100644 --- a/domains/ai-alignment/international-humanitarian-law-and-ai-alignment-converge-on-explainability-requirements.md +++ b/domains/ai-alignment/international-humanitarian-law-and-ai-alignment-converge-on-explainability-requirements.md @@ -19,8 +19,10 @@ 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'} +- 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 --- # International humanitarian law and AI alignment research independently converged on the same technical limitation that autonomous systems cannot be adequately predicted understood or explained diff --git a/domains/health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md b/domains/health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md index 299a3f182..df9903c0d 100644 --- a/domains/health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md +++ b/domains/health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md @@ -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 diff --git a/domains/health/ai-induced-deskilling-follows-consistent-cross-specialty-pattern-in-medicine.md b/domains/health/ai-induced-deskilling-follows-consistent-cross-specialty-pattern-in-medicine.md index 7bf2fcf05..98bc83c68 100644 --- a/domains/health/ai-induced-deskilling-follows-consistent-cross-specialty-pattern-in-medicine.md +++ b/domains/health/ai-induced-deskilling-follows-consistent-cross-specialty-pattern-in-medicine.md @@ -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 +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 +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 --- # 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 diff --git a/domains/health/clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling.md b/domains/health/clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling.md index abcedf4ec..ea57fc769 100644 --- a/domains/health/clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling.md +++ b/domains/health/clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling.md @@ -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 diff --git a/domains/health/comprehensive-behavioral-wraparound-enables-durable-weight-maintenance-post-glp1-cessation.md b/domains/health/comprehensive-behavioral-wraparound-enables-durable-weight-maintenance-post-glp1-cessation.md index 2769f0ed0..85c52390b 100644 --- a/domains/health/comprehensive-behavioral-wraparound-enables-durable-weight-maintenance-post-glp1-cessation.md +++ b/domains/health/comprehensive-behavioral-wraparound-enables-durable-weight-maintenance-post-glp1-cessation.md @@ -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 diff --git a/domains/health/digital-behavioral-support-enables-glp1-dose-reduction-while-maintaining-clinical-outcomes.md b/domains/health/digital-behavioral-support-enables-glp1-dose-reduction-while-maintaining-clinical-outcomes.md index 038914dda..eb285d7a1 100644 --- a/domains/health/digital-behavioral-support-enables-glp1-dose-reduction-while-maintaining-clinical-outcomes.md +++ b/domains/health/digital-behavioral-support-enables-glp1-dose-reduction-while-maintaining-clinical-outcomes.md @@ -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 diff --git a/domains/health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md b/domains/health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md index 136400061..4f58f1d49 100644 --- a/domains/health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md +++ b/domains/health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md @@ -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 diff --git a/domains/health/fda-maude-cannot-identify-ai-contributions-to-adverse-events-due-to-structural-reporting-gaps.md b/domains/health/fda-maude-cannot-identify-ai-contributions-to-adverse-events-due-to-structural-reporting-gaps.md index e7390293a..01604678d 100644 --- a/domains/health/fda-maude-cannot-identify-ai-contributions-to-adverse-events-due-to-structural-reporting-gaps.md +++ b/domains/health/fda-maude-cannot-identify-ai-contributions-to-adverse-events-due-to-structural-reporting-gaps.md @@ -13,6 +13,7 @@ related_claims: ["[[healthcare AI regulation needs blank-sheet redesign because supports: - {'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"} - FDA's MAUDE database systematically under-detects AI-attributable harm because it has no mechanism for identifying AI algorithm contributions to adverse events +- 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 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|2026-04-07"} - FDA's MAUDE database systematically under-detects AI-attributable harm because it has no mechanism for identifying AI algorithm contributions to adverse events|supports|2026-04-07 @@ -22,6 +23,7 @@ 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 diff --git a/domains/health/fda-maude-database-lacks-ai-specific-adverse-event-fields-creating-systematic-under-detection-of-ai-attributable-harm.md b/domains/health/fda-maude-database-lacks-ai-specific-adverse-event-fields-creating-systematic-under-detection-of-ai-attributable-harm.md index 3bf236bbb..3daab06dd 100644 --- a/domains/health/fda-maude-database-lacks-ai-specific-adverse-event-fields-creating-systematic-under-detection-of-ai-attributable-harm.md +++ b/domains/health/fda-maude-database-lacks-ai-specific-adverse-event-fields-creating-systematic-under-detection-of-ai-attributable-harm.md @@ -13,6 +13,7 @@ related_claims: ["[[human-in-the-loop clinical AI degrades to worse-than-AI-alon supports: - {'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"} - 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 +- 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 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|2026-04-07"} - 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|supports|2026-04-07 @@ -22,6 +23,7 @@ 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 diff --git a/domains/health/glp-1-access-structure-inverts-need-creating-equity-paradox.md b/domains/health/glp-1-access-structure-inverts-need-creating-equity-paradox.md index 437c683c9..83944c001 100644 --- a/domains/health/glp-1-access-structure-inverts-need-creating-equity-paradox.md +++ b/domains/health/glp-1-access-structure-inverts-need-creating-equity-paradox.md @@ -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 +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 +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 --- # 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 diff --git a/domains/health/glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md b/domains/health/glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md index 0d20e2584..0fbb1bb2b 100644 --- a/domains/health/glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md +++ b/domains/health/glp-1-persistence-drops-to-15-percent-at-two-years-for-non-diabetic-obesity-patients-undermining-chronic-use-economics.md @@ -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 diff --git a/domains/health/glp-1-population-mortality-impact-delayed-20-years-by-access-and-adherence-constraints.md b/domains/health/glp-1-population-mortality-impact-delayed-20-years-by-access-and-adherence-constraints.md index b7ba636ca..4f7effa94 100644 --- a/domains/health/glp-1-population-mortality-impact-delayed-20-years-by-access-and-adherence-constraints.md +++ b/domains/health/glp-1-population-mortality-impact-delayed-20-years-by-access-and-adherence-constraints.md @@ -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 --- diff --git a/domains/health/glp-1-receptor-agonists-require-continuous-treatment-because-metabolic-benefits-reverse-within-28-52-weeks-of-discontinuation.md b/domains/health/glp-1-receptor-agonists-require-continuous-treatment-because-metabolic-benefits-reverse-within-28-52-weeks-of-discontinuation.md index b5eebf4c8..19e749fdf 100644 --- a/domains/health/glp-1-receptor-agonists-require-continuous-treatment-because-metabolic-benefits-reverse-within-28-52-weeks-of-discontinuation.md +++ b/domains/health/glp-1-receptor-agonists-require-continuous-treatment-because-metabolic-benefits-reverse-within-28-52-weeks-of-discontinuation.md @@ -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 diff --git a/domains/health/glp1-access-follows-systematic-inversion-highest-burden-states-have-lowest-coverage-and-highest-income-relative-cost.md b/domains/health/glp1-access-follows-systematic-inversion-highest-burden-states-have-lowest-coverage-and-highest-income-relative-cost.md index 59cf6f852..16204e0a9 100644 --- a/domains/health/glp1-access-follows-systematic-inversion-highest-burden-states-have-lowest-coverage-and-highest-income-relative-cost.md +++ b/domains/health/glp1-access-follows-systematic-inversion-highest-burden-states-have-lowest-coverage-and-highest-income-relative-cost.md @@ -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 diff --git a/domains/health/lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md b/domains/health/lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md index 73d996722..a313d2931 100644 --- a/domains/health/lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md +++ b/domains/health/lower-income-patients-show-higher-glp-1-discontinuation-rates-suggesting-affordability-not-just-clinical-factors-drive-persistence.md @@ -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 diff --git a/domains/health/never-skilling-is-detection-resistant-and-unrecoverable-making-it-worse-than-deskilling.md b/domains/health/never-skilling-is-detection-resistant-and-unrecoverable-making-it-worse-than-deskilling.md index 42208d0b7..a93d576af 100644 --- a/domains/health/never-skilling-is-detection-resistant-and-unrecoverable-making-it-worse-than-deskilling.md +++ b/domains/health/never-skilling-is-detection-resistant-and-unrecoverable-making-it-worse-than-deskilling.md @@ -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 diff --git a/domains/health/never-skilling-is-structurally-invisible-because-it-lacks-pre-ai-baseline-requiring-prospective-competency-assessment.md b/domains/health/never-skilling-is-structurally-invisible-because-it-lacks-pre-ai-baseline-requiring-prospective-competency-assessment.md index 75612e26e..47ce3e1f6 100644 --- a/domains/health/never-skilling-is-structurally-invisible-because-it-lacks-pre-ai-baseline-requiring-prospective-competency-assessment.md +++ b/domains/health/never-skilling-is-structurally-invisible-because-it-lacks-pre-ai-baseline-requiring-prospective-competency-assessment.md @@ -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 diff --git a/domains/health/wealth-stratified-glp1-access-creates-disease-progression-disparity-with-lowest-income-black-patients-treated-at-13-percent-higher-bmi.md b/domains/health/wealth-stratified-glp1-access-creates-disease-progression-disparity-with-lowest-income-black-patients-treated-at-13-percent-higher-bmi.md index 8eee21a8b..1e02b6f1f 100644 --- a/domains/health/wealth-stratified-glp1-access-creates-disease-progression-disparity-with-lowest-income-black-patients-treated-at-13-percent-higher-bmi.md +++ b/domains/health/wealth-stratified-glp1-access-creates-disease-progression-disparity-with-lowest-income-black-patients-treated-at-13-percent-higher-bmi.md @@ -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 diff --git a/domains/space-development/clps-mechanism-solved-viper-procurement-problem-through-vehicle-flexibility.md b/domains/space-development/clps-mechanism-solved-viper-procurement-problem-through-vehicle-flexibility.md index 4fa79be76..147d1fe13 100644 --- a/domains/space-development/clps-mechanism-solved-viper-procurement-problem-through-vehicle-flexibility.md +++ b/domains/space-development/clps-mechanism-solved-viper-procurement-problem-through-vehicle-flexibility.md @@ -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 diff --git a/domains/space-development/clps-transforms-from-demonstration-to-lunar-logistics-baseline-under-project-ignition.md b/domains/space-development/clps-transforms-from-demonstration-to-lunar-logistics-baseline-under-project-ignition.md index 0e8db0f55..67a3ad36a 100644 --- a/domains/space-development/clps-transforms-from-demonstration-to-lunar-logistics-baseline-under-project-ignition.md +++ b/domains/space-development/clps-transforms-from-demonstration-to-lunar-logistics-baseline-under-project-ignition.md @@ -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