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reweave: 2026 04 07 #2493

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m3taversal wants to merge 1 commit from reweave/2026-04-07 into main
pull from: reweave/2026-04-07
merge into: teleo:main
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m3taversal commented 2026-04-07 09:14:09 +00:00
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m3taversal added 1 commit 2026-04-07 09:14:09 +00:00 
Threshold: 0.7, Haiku classification, 30 files modified.

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m3taversal commented 2026-04-07 09:14:12 +00:00
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Thanks for the contribution! Your PR is queued for evaluation (priority: high). Expected review time: ~5 minutes.

This is an automated message from the Teleo pipeline.

Thanks for the contribution! Your PR is queued for evaluation (priority: high). Expected review time: ~5 minutes. _This is an automated message from the Teleo pipeline._
m3taversal commented 2026-04-07 09:14:26 +00:00
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Validation: PASS — 0/0 claims pass

tier0-gate v2 | 2026-04-07 09:14 UTC

<!-- TIER0-VALIDATION:4d9fb53f596af413861df08ee8ec0bd13b1696e4 --> **Validation: PASS** — 0/0 claims pass *tier0-gate v2 | 2026-04-07 09:14 UTC*
m3taversal commented 2026-04-07 09:14:56 +00:00
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Auto-approved: reweave structural update (frontmatter edges only). Leo reviews manually.

Auto-approved: reweave structural update (frontmatter edges only). Leo reviews manually.
leo commented 2026-04-07 09:16:12 +00:00
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Eval started — 2 reviewers: leo (cross-domain, opus), vida (domain-peer, sonnet)

teleo-eval-orchestrator v2

**Eval started** — 2 reviewers: leo (cross-domain, opus), vida (domain-peer, sonnet) *teleo-eval-orchestrator v2*
leo commented 2026-04-07 09:19:16 +00:00
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Leo Cross-Domain Review — PR #2493

Branch: reweave/2026-04-07
Commits: 2 (merge 30 files via frontmatter union + connect 19 orphan claims via vector similarity)
Scope: 30 files changed, 118 insertions, 0 deletions. Adds supports, related, and reweave_edges frontmatter to existing claims across health (22), space-development (7), grand-strategy (1), and entities (1).

Issues

1. Broken entity links masquerading as claim support (3 files)

Three space-development claims add supports: - Aetherflux with corresponding reweave_edges: - Aetherflux|supports|2026-04-07:

  • breakthrough-energy-ventures-investment-in-orbital-solar-infrastructure-signals-sbsp-credibility-as-climate-technology-category.md
  • orbital-data-centers-and-space-based-solar-power-share-identical-infrastructure-requirements-creating-dual-use-revenue-bridge.md
  • space-based-solar-power-and-orbital-data-centers-share-infrastructure-making-odc-the-near-term-revenue-bridge-to-long-term-sbsp.md

"Aetherflux" is an entity, not a claim. The supports field should link claims to claims. If the intent is to track which claims reference Aetherflux, that belongs in related_claims or a new entities field — not supports. Same issue with supports: - UK House of Lords Science and Technology Committee in the UK-EU-US convergence claim.

Fix: Remove these 4 entity-as-claim links. If entity tracking is needed, propose a schema extension.

2. Broken link to clinical trial ID (1 file)

human-in-the-loop clinical AI degrades... adds supports: - NCT07328815 - Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning. This is a ClinicalTrials.gov identifier, not a claim in the KB. The reweave created a dead link.

Fix: Remove, or convert to a related_claims wiki-link if a corresponding claim exists.

3. Duplicate supports entries in mixed formats (2 files)

Both FDA MAUDE claims already had dict-style supports entries:

supports:
- {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion..."}

The reweave appends the same link as a flat string:

- The clinical AI safety gap is doubly structural: FDA enforcement discretion...

This creates duplicate edges in incompatible formats. The dict format is itself non-standard — it should be resolved to one format, not doubled.

Fix: Normalize to flat string format and deduplicate. The dict-style entries are a pre-existing issue but this PR makes it worse by adding a second representation of the same link.

4. Field ordering inconsistency (1 file)

In regulatory-deregulation-occurring-during-active-harm-accumulation, the new related: field appears after reweave_edges:. Every other file in this PR places related: before or alongside supports:. Minor, but the reweave tooling should be consistent.

Observations (not blocking)

Semantic accuracy is generally good. The vector similarity approach produced sensible connections:

  • CVD cluster: bifurcation → hypertension shift → midlife reversal → heart failure. Causal chain is well-linked.
  • Regulatory cluster: deregulation → rollback → vacuum → convergence. The four regulatory claims form a coherent escalation sequence.
  • GLP-1 cluster: Cipla hedging → tirzepatide patent thicket → Indian generics. Market structure connections are correct.
  • UPF cluster: inflammation → hypertension → treatment failure. Bidirectional supports links correctly model the causal chain.
  • Space stations cluster: commercial stations → anchor customer uncertainty → Phase 2 freeze impact → policy-driven delays. Good.

One edge direction is debatable: cvd-stagnation-drives-us-life-expectancy-plateau is marked as supports for midlife CVD mortality reversal. The causal direction is arguably reversed — midlife reversal is the more granular finding that supports the broader stagnation claim, not the other way around. Not blocking, but worth noting for future reweave calibration.

Pre-existing near-duplicate not addressed: The two ODC-SBSP claims (orbital-data-centers-and-space-based-solar-power-share-identical-infrastructure-requirements... and space-based-solar-power-and-orbital-data-centers-share-infrastructure...) argue the same thesis with different source emphases. The reweave connected them to the same entity ("Aetherflux") but didn't flag them as candidates for merge. This is an opportunity for the next reweave pass.

Verdict: request_changes
Model: opus
Summary: Reweave edges are semantically sound across ~25 of 30 files, but 5 files have broken links (entities and a clinical trial ID used as claim supports targets) and 2 files have duplicate edges in mixed formats. Fix the 5 broken links, deduplicate the MAUDE entries, and this is ready to merge.

# Leo Cross-Domain Review — PR #2493 **Branch:** reweave/2026-04-07 **Commits:** 2 (merge 30 files via frontmatter union + connect 19 orphan claims via vector similarity) **Scope:** 30 files changed, 118 insertions, 0 deletions. Adds `supports`, `related`, and `reweave_edges` frontmatter to existing claims across health (22), space-development (7), grand-strategy (1), and entities (1). --- ## Issues ### 1. Broken entity links masquerading as claim support (3 files) Three space-development claims add `supports: - Aetherflux` with corresponding `reweave_edges: - Aetherflux|supports|2026-04-07`: - `breakthrough-energy-ventures-investment-in-orbital-solar-infrastructure-signals-sbsp-credibility-as-climate-technology-category.md` - `orbital-data-centers-and-space-based-solar-power-share-identical-infrastructure-requirements-creating-dual-use-revenue-bridge.md` - `space-based-solar-power-and-orbital-data-centers-share-infrastructure-making-odc-the-near-term-revenue-bridge-to-long-term-sbsp.md` "Aetherflux" is an entity, not a claim. The `supports` field should link claims to claims. If the intent is to track which claims reference Aetherflux, that belongs in `related_claims` or a new `entities` field — not `supports`. Same issue with `supports: - UK House of Lords Science and Technology Committee` in the UK-EU-US convergence claim. **Fix:** Remove these 4 entity-as-claim links. If entity tracking is needed, propose a schema extension. ### 2. Broken link to clinical trial ID (1 file) `human-in-the-loop clinical AI degrades...` adds `supports: - NCT07328815 - Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning`. This is a ClinicalTrials.gov identifier, not a claim in the KB. The reweave created a dead link. **Fix:** Remove, or convert to a `related_claims` wiki-link if a corresponding claim exists. ### 3. Duplicate supports entries in mixed formats (2 files) Both FDA MAUDE claims already had dict-style supports entries: ```yaml supports: - {'The clinical AI safety gap is doubly structural': "FDA enforcement discretion..."} ``` The reweave appends the same link as a flat string: ```yaml - The clinical AI safety gap is doubly structural: FDA enforcement discretion... ``` This creates duplicate edges in incompatible formats. The dict format is itself non-standard — it should be resolved to one format, not doubled. **Fix:** Normalize to flat string format and deduplicate. The dict-style entries are a pre-existing issue but this PR makes it worse by adding a second representation of the same link. ### 4. Field ordering inconsistency (1 file) In `regulatory-deregulation-occurring-during-active-harm-accumulation`, the new `related:` field appears after `reweave_edges:`. Every other file in this PR places `related:` before or alongside `supports:`. Minor, but the reweave tooling should be consistent. ## Observations (not blocking) **Semantic accuracy is generally good.** The vector similarity approach produced sensible connections: - CVD cluster: bifurcation → hypertension shift → midlife reversal → heart failure. Causal chain is well-linked. - Regulatory cluster: deregulation → rollback → vacuum → convergence. The four regulatory claims form a coherent escalation sequence. - GLP-1 cluster: Cipla hedging → tirzepatide patent thicket → Indian generics. Market structure connections are correct. - UPF cluster: inflammation → hypertension → treatment failure. Bidirectional `supports` links correctly model the causal chain. - Space stations cluster: commercial stations → anchor customer uncertainty → Phase 2 freeze impact → policy-driven delays. Good. **One edge direction is debatable:** `cvd-stagnation-drives-us-life-expectancy-plateau` is marked as `supports` for midlife CVD mortality reversal. The causal direction is arguably reversed — midlife reversal is the more granular finding that supports the broader stagnation claim, not the other way around. Not blocking, but worth noting for future reweave calibration. **Pre-existing near-duplicate not addressed:** The two ODC-SBSP claims (`orbital-data-centers-and-space-based-solar-power-share-identical-infrastructure-requirements...` and `space-based-solar-power-and-orbital-data-centers-share-infrastructure...`) argue the same thesis with different source emphases. The reweave connected them to the same entity ("Aetherflux") but didn't flag them as candidates for merge. This is an opportunity for the next reweave pass. --- **Verdict:** request_changes **Model:** opus **Summary:** Reweave edges are semantically sound across ~25 of 30 files, but 5 files have broken links (entities and a clinical trial ID used as claim `supports` targets) and 2 files have duplicate edges in mixed formats. Fix the 5 broken links, deduplicate the MAUDE entries, and this is ready to merge. <!-- VERDICT:LEO:REQUEST_CHANGES -->
vida commented 2026-04-07 09:20:47 +00:00
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Vida Domain Peer Review — PR #2493

Reviewed as health domain specialist. 22 health claims across four thematic clusters: CVD/cardiometabolic, clinical AI regulatory, UPF/hypertension mechanism, and pharma strategy.

CVD / Cardiometabolic Cluster (8 claims)

Strong cluster. The bifurcation story (ischemic declining, heart failure and hypertensive disease rising to all-time highs) is epidemiologically sound and AHA 2026 is the right primary source. The Shiels et al. PNAS 2020 citation for the 3-11x CVD vs. drug-death life expectancy comparison is legitimate — the range reflects the sex difference (11x women, ~3x men based on 1.14 vs 0.1 and 1.14 vs 0.4 years respectively), which is worth making explicit in the body.

Data inconsistency that needs resolution: The existing KB claim hypertension-related-cvd-mortality-doubled-2000-2023-despite-available-treatment (from JACC 2025) reports hypertensive disease mortality rising from ~23 to 43+ per 100k. The new PR claim hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022 (from AHA 2026) reports 15.8 to 31.9 per 100k. Both claim AHA/JACC data for roughly the same period. The discrepancy (baseline 23 vs 15.8; peak 43+ vs 31.9) is materially large and will confuse anyone trying to track this number. The most likely explanation is that the existing claim uses "primary or contributing cause" while the new claims use "age-adjusted mortality for hypertensive disease as primary cause" — but this isn't stated. One of the two claims should acknowledge the methodological difference or both should harmonize to a single measurement definition.

Missing connections in the CVD cluster: The hypertension and CVD stagnation claims don't link to glp-1-multi-organ-protection-creates-compounding-value-across-kidney-cardiovascular-and-metabolic-endpoints — GLP-1s are the emerging therapeutic category most directly targeted at exactly the metabolic disease driving these trends. This is a significant missing connection. The AHA 2026 data is the strongest current evidence for GLP-1 market need, and vice versa.

UPF/Hypertension Mechanism (2 claims)

The ultra-processed-food-consumption-increases-incident-hypertension claim is well-evidenced: REGARDS cohort with 9.3-year follow-up plus ELSA-Brasil replication is legitimate. likely confidence is calibrated correctly. Good that it acknowledges the racial measurement difference (% kcal vs % grams significant in different populations) — this is real and important for interpretation.

One technical concern in the mechanistic claim: upf-driven-chronic-inflammation-creates-continuous-vascular-risk-regeneration-explaining-antihypertensive-treatment-failure states "76.6% of treated patients fail to achieve blood pressure control" as a fact with no direct citation — the source frontmatter says "(inferential connection)." The 76.6% figure is consistent with only-23-percent-of-treated-us-hypertensives-achieve-blood-pressure-control already in the KB, which the Relevant Notes section references. So the number is at least grounded, but the body should cite it explicitly rather than treating it as assumed. The claim also doesn't acknowledge competing explanations for treatment failure (medication non-adherence, white-coat hypertension, dose inadequacy) — it frames UPF inflammation as the explanation for the 76.6%, which overstates the inferential leap. experimental confidence is appropriate, but the body should scope this as "contributes to" or "partially explains" rather than "explaining why."

The GLP-1 anti-inflammatory pathway invoked at the end of this claim is clever — semaglutide's 67% cardiovascular benefit independent of weight loss via hsCRP reduction as mirror evidence for the UPF inflammation mechanism. This is good analogical reasoning and appropriately flagged as complementary evidence.

Clinical AI Regulatory Cluster (7 claims including MAUDE pair)

The MAUDE pair (fda-maude-cannot-identify-ai-contributions and fda-maude-database-lacks-ai-specific-adverse-event-fields) are genuinely distinct: one is about causal attribution failure (can we tell if AI caused the harm — Handley et al.), the other is about structural surveillance architecture (the database has no AI fields — Babic et al.). Both are experimental and appropriately so — the 943 adverse events over 13 years as evidence of surveillance failure (not safety) is a strong and defensible interpretation.

The FDA co-authorship point in fda-maude-cannot-identify-ai-contributions (Krevat works in FDA's patient safety program) is genuinely notable and worth including — it's not just academic criticism, it's FDA insiders documenting their own tool's inadequacy.

Cluster density note: Five claims cover overlapping evidence from the same 60-day regulatory window (FDA CDS expansion Jan 2026, EU AI Act rollback Dec 2025). Each makes a distinct argument — timing paradox, institutional epistemic divergence, convergence pattern, regulatory capture framing — so I won't call this a duplicate problem. But the regulatory-rollback-clinical-ai-eu-us-2025-2026 claim uses the phrase "coordinated or parallel regulatory capture." "Regulatory capture" has a specific meaning (regulators serve industry interests over public interests) and the evidence supports "parallel deregulation responding to industry lobbying," which is meaningfully different from regulatory capture in the technical sense. The hedged framing ("coordinated or parallel") is defensible but editors should know this is an interpretive conclusion, not empirically demonstrated.

Confidence concern: multi-agent-clinical-ai-reduces-computational-cost-65x is rated proven. This is a single Mount Sinai study (March 2026). Single-site, single-study for a proven rating is aggressive for a performance claim that will generalize across health systems with different task mixes, EHR architectures, and patient populations. likely is more defensible.

Pharma / Access Claims

Both cipla-dual-role and indian-generic-semaglutide-exports-enabled-by-evergreening-rejection are well-constructed. The Delhi High Court evergreening rejection framing is technically accurate — rejecting secondary patents under India's Section 3(d) is distinct from normal patent expiry, and the claim correctly identifies this as creating the access pathway. experimental for both is appropriate given the market evolution is still in early stages.

The Cipla dual-role claim is a genuine strategic observation not in the KB. Good non-US claim.

Cross-Domain Connections Worth Noting

The clinical AI regulatory cluster is directly relevant to Theseus — the regulatory-vacuum-emerges claim describes institutional epistemic divergence between WHO (accumulating safety evidence) and EU Commission (responding to industry lobbying) that is a concrete instance of the governance failure modes Theseus studies. The UK-EU-US convergence on adoption acceleration is a policy-level version of the human oversight degradation Theseus tracks.

The UPF → hypertension mechanism claims strengthen the case for Clay's food environment / narrative infrastructure work — specifically that dietary behavior change is a narrative problem not just an information problem, since the UPF-treatment failure mechanism shows even adherent patients fail when food environment doesn't change.

Summary of Issues

Issue Severity File
Hypertension mortality numbers inconsistent between new claims (15.8→31.9) and existing KB (23→43+) Should resolve hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022.md + existing claim
76.6% treatment failure stat uncited in body Minor upf-driven-chronic-inflammation-creates-continuous-vascular-risk-regeneration-explaining-antihypertensive-treatment-failure.md
65x cost reduction rated proven on single-site study Minor calibration multi-agent-clinical-ai-reduces-computational-cost-65x-while-maintaining-performance-under-workload.md
GLP-1 multi-organ protection not linked in CVD cluster Missing connection hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022.md, cvd-stagnation-drives-us-life-expectancy-plateau.md

The data inconsistency in hypertension numbers is the only item that rises above cosmetic. The rest are calibration and completeness notes that don't block merge.

Verdict: approve
Model: sonnet
Summary: High-quality, well-evidenced contribution. CVD bifurcation cluster and UPF mechanism claims are the strongest additions — grounded in AHA 2026 and REGARDS cohort data respectively. One data inconsistency (hypertension mortality absolute numbers differ between new and existing claims, likely a primary-vs-contributing cause measurement difference) should be resolved before merge or acknowledged explicitly. The 65x computational efficiency claim is rated proven on single-site evidence; likely is more calibrated. Strong non-US claims (India/EU) address a documented KB gap.

# Vida Domain Peer Review — PR #2493 Reviewed as health domain specialist. 22 health claims across four thematic clusters: CVD/cardiometabolic, clinical AI regulatory, UPF/hypertension mechanism, and pharma strategy. --- ## CVD / Cardiometabolic Cluster (8 claims) Strong cluster. The bifurcation story (ischemic declining, heart failure and hypertensive disease rising to all-time highs) is epidemiologically sound and AHA 2026 is the right primary source. The Shiels et al. PNAS 2020 citation for the 3-11x CVD vs. drug-death life expectancy comparison is legitimate — the range reflects the sex difference (11x women, ~3x men based on 1.14 vs 0.1 and 1.14 vs 0.4 years respectively), which is worth making explicit in the body. **Data inconsistency that needs resolution:** The existing KB claim `hypertension-related-cvd-mortality-doubled-2000-2023-despite-available-treatment` (from JACC 2025) reports hypertensive disease mortality rising from ~23 to 43+ per 100k. The new PR claim `hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022` (from AHA 2026) reports 15.8 to 31.9 per 100k. Both claim AHA/JACC data for roughly the same period. The discrepancy (baseline 23 vs 15.8; peak 43+ vs 31.9) is materially large and will confuse anyone trying to track this number. The most likely explanation is that the existing claim uses "primary or contributing cause" while the new claims use "age-adjusted mortality for hypertensive disease as primary cause" — but this isn't stated. One of the two claims should acknowledge the methodological difference or both should harmonize to a single measurement definition. **Missing connections in the CVD cluster**: The hypertension and CVD stagnation claims don't link to `glp-1-multi-organ-protection-creates-compounding-value-across-kidney-cardiovascular-and-metabolic-endpoints` — GLP-1s are the emerging therapeutic category most directly targeted at exactly the metabolic disease driving these trends. This is a significant missing connection. The AHA 2026 data is the strongest current evidence for GLP-1 market need, and vice versa. --- ## UPF/Hypertension Mechanism (2 claims) The `ultra-processed-food-consumption-increases-incident-hypertension` claim is well-evidenced: REGARDS cohort with 9.3-year follow-up plus ELSA-Brasil replication is legitimate. `likely` confidence is calibrated correctly. Good that it acknowledges the racial measurement difference (% kcal vs % grams significant in different populations) — this is real and important for interpretation. **One technical concern in the mechanistic claim**: `upf-driven-chronic-inflammation-creates-continuous-vascular-risk-regeneration-explaining-antihypertensive-treatment-failure` states "76.6% of treated patients fail to achieve blood pressure control" as a fact with no direct citation — the source frontmatter says "(inferential connection)." The 76.6% figure is consistent with `only-23-percent-of-treated-us-hypertensives-achieve-blood-pressure-control` already in the KB, which the Relevant Notes section references. So the number is at least grounded, but the body should cite it explicitly rather than treating it as assumed. The claim also doesn't acknowledge competing explanations for treatment failure (medication non-adherence, white-coat hypertension, dose inadequacy) — it frames UPF inflammation as *the* explanation for the 76.6%, which overstates the inferential leap. `experimental` confidence is appropriate, but the body should scope this as "contributes to" or "partially explains" rather than "explaining why." The GLP-1 anti-inflammatory pathway invoked at the end of this claim is clever — semaglutide's 67% cardiovascular benefit independent of weight loss via hsCRP reduction as mirror evidence for the UPF inflammation mechanism. This is good analogical reasoning and appropriately flagged as complementary evidence. --- ## Clinical AI Regulatory Cluster (7 claims including MAUDE pair) The MAUDE pair (`fda-maude-cannot-identify-ai-contributions` and `fda-maude-database-lacks-ai-specific-adverse-event-fields`) are genuinely distinct: one is about causal attribution failure (can we tell if AI caused the harm — Handley et al.), the other is about structural surveillance architecture (the database has no AI fields — Babic et al.). Both are `experimental` and appropriately so — the 943 adverse events over 13 years as evidence of surveillance failure (not safety) is a strong and defensible interpretation. The FDA co-authorship point in `fda-maude-cannot-identify-ai-contributions` (Krevat works in FDA's patient safety program) is genuinely notable and worth including — it's not just academic criticism, it's FDA insiders documenting their own tool's inadequacy. **Cluster density note**: Five claims cover overlapping evidence from the same 60-day regulatory window (FDA CDS expansion Jan 2026, EU AI Act rollback Dec 2025). Each makes a distinct argument — timing paradox, institutional epistemic divergence, convergence pattern, regulatory capture framing — so I won't call this a duplicate problem. But the `regulatory-rollback-clinical-ai-eu-us-2025-2026` claim uses the phrase "coordinated or parallel regulatory capture." "Regulatory capture" has a specific meaning (regulators serve industry interests over public interests) and the evidence supports "parallel deregulation responding to industry lobbying," which is meaningfully different from regulatory capture in the technical sense. The hedged framing ("coordinated or parallel") is defensible but editors should know this is an interpretive conclusion, not empirically demonstrated. **Confidence concern**: `multi-agent-clinical-ai-reduces-computational-cost-65x` is rated `proven`. This is a single Mount Sinai study (March 2026). Single-site, single-study for a `proven` rating is aggressive for a performance claim that will generalize across health systems with different task mixes, EHR architectures, and patient populations. `likely` is more defensible. --- ## Pharma / Access Claims Both `cipla-dual-role` and `indian-generic-semaglutide-exports-enabled-by-evergreening-rejection` are well-constructed. The Delhi High Court evergreening rejection framing is technically accurate — rejecting secondary patents under India's Section 3(d) is distinct from normal patent expiry, and the claim correctly identifies this as creating the access pathway. `experimental` for both is appropriate given the market evolution is still in early stages. The Cipla dual-role claim is a genuine strategic observation not in the KB. Good non-US claim. --- ## Cross-Domain Connections Worth Noting The clinical AI regulatory cluster is directly relevant to Theseus — the `regulatory-vacuum-emerges` claim describes institutional epistemic divergence between WHO (accumulating safety evidence) and EU Commission (responding to industry lobbying) that is a concrete instance of the governance failure modes Theseus studies. The UK-EU-US convergence on adoption acceleration is a policy-level version of the human oversight degradation Theseus tracks. The UPF → hypertension mechanism claims strengthen the case for Clay's food environment / narrative infrastructure work — specifically that dietary behavior change is a narrative problem not just an information problem, since the UPF-treatment failure mechanism shows even adherent patients fail when food environment doesn't change. --- ## Summary of Issues | Issue | Severity | File | |-------|----------|------| | Hypertension mortality numbers inconsistent between new claims (15.8→31.9) and existing KB (23→43+) | Should resolve | `hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022.md` + existing claim | | 76.6% treatment failure stat uncited in body | Minor | `upf-driven-chronic-inflammation-creates-continuous-vascular-risk-regeneration-explaining-antihypertensive-treatment-failure.md` | | 65x cost reduction rated `proven` on single-site study | Minor calibration | `multi-agent-clinical-ai-reduces-computational-cost-65x-while-maintaining-performance-under-workload.md` | | GLP-1 multi-organ protection not linked in CVD cluster | Missing connection | `hypertension-shifted-from-secondary-to-primary-cvd-mortality-driver-since-2022.md`, `cvd-stagnation-drives-us-life-expectancy-plateau.md` | The data inconsistency in hypertension numbers is the only item that rises above cosmetic. The rest are calibration and completeness notes that don't block merge. --- **Verdict:** approve **Model:** sonnet **Summary:** High-quality, well-evidenced contribution. CVD bifurcation cluster and UPF mechanism claims are the strongest additions — grounded in AHA 2026 and REGARDS cohort data respectively. One data inconsistency (hypertension mortality absolute numbers differ between new and existing claims, likely a primary-vs-contributing cause measurement difference) should be resolved before merge or acknowledged explicitly. The 65x computational efficiency claim is rated `proven` on single-site evidence; `likely` is more calibrated. Strong non-US claims (India/EU) address a documented KB gap. <!-- VERDICT:VIDA:APPROVE -->
leo commented 2026-04-07 09:20:48 +00:00
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Changes requested by leo(cross-domain). Address feedback and push to trigger re-eval.

teleo-eval-orchestrator v2

**Changes requested** by leo(cross-domain). Address feedback and push to trigger re-eval. *teleo-eval-orchestrator v2*
m3taversal closed this pull request 2026-04-07 09:31:18 +00:00
m3taversal commented 2026-04-07 09:31:18 +00:00
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Closed by conflict auto-resolver: rebase failed 3 times (enrichment conflict). Claims already on main from prior extraction. Source filed in archive.

Closed by conflict auto-resolver: rebase failed 3 times (enrichment conflict). Claims already on main from prior extraction. Source filed in archive.

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Reference: teleo/teleo-codex#2493
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