cschanhniem · Jun 28, 2026 · Jun 28, 2026 · Jun 28, 2026 · Jun 28, 2026
diff --git a/agent-radar.json b/agent-radar.json
@@ -52,6 +52,22 @@
         "tasks_file": "problem-packs/public-health/birth-registration-access-global/tasks.json",
         "why_pick_now": "Completing this scoped task opens 5 follow-on tasks across 4 additional roles."
       },
+      {
+        "pack_id": "public-health/oral-health-access-global",
+        "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries",
+        "task_id": "source-inventory",
+        "title": "Inventory data sources for public-health/oral-health-access-global",
+        "owner_role": "literature-scout",
+        "reviewer_needed": "domain-reviewer",
+        "safety_risk": "low",
+        "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.",
+        "evidence_count": 5,
+        "downstream_tasks_unlocked": 4,
+        "downstream_high_risk_tasks": 2,
+        "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md",
+        "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json",
+        "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles."
+      },
       {
         "pack_id": "education/digital-divide-school-access-global",
         "pack_title": "Digital Divide Measurement And School Internet Connectivity In Low-Income Countries",
@@ -100,22 +116,6 @@
         "tasks_file": "problem-packs/public-health/ncd-risk-factor-surveillance-global/tasks.json",
         "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles."
       },
-      {
-        "pack_id": "public-health/oral-health-access-global",
-        "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries",
-        "task_id": "source-inventory",
-        "title": "Inventory data sources for public-health/oral-health-access-global",
-        "owner_role": "literature-scout",
-        "reviewer_needed": "domain-reviewer",
-        "safety_risk": "low",
-        "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.",
-        "evidence_count": 1,
-        "downstream_tasks_unlocked": 4,
-        "downstream_high_risk_tasks": 2,
-        "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md",
-        "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json",
-        "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles."
-      },
       {
         "pack_id": "climate-health/malaria-early-warning-africa",
         "pack_title": "Malaria Early Warning Signals In Sub-Saharan Africa",

diff --git a/docs/wiki/Agent-Radar.md b/docs/wiki/Agent-Radar.md
@@ -37,7 +37,19 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris
 - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles.
 - Done condition: At least six candidate sources are classified as usable, limited, or rejected with explicit reasons covering measure family, timing, geographic grain, and health-linkage relevance.
 
-### 2. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries
+### 2. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries
+
+- Pack: [`public-health/oral-health-access-global`](../../problem-packs/public-health/oral-health-access-global/problem.md)
+- Task: `source-inventory` — Inventory data sources for public-health/oral-health-access-global
+- Risk: `low`
+- Reviewer needed: `domain-reviewer`
+- Existing evidence records: 5
+- Downstream tasks unlocked: 4
+- Downstream high-risk tasks: 2
+- Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles.
+- Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons.
+
+### 3. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries
 
 - Pack: [`education/digital-divide-school-access-global`](../../problem-packs/education/digital-divide-school-access-global/problem.md)
 - Task: `source-inventory` — Inventory school connectivity, mobile-network, and digital-learning data sources for low-income countries
@@ -49,7 +61,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris
 - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles.
 - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering connectivity-classification methodology, data currency, and cross-validation status.
 
-### 3. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries
+### 4. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries
 
 - Pack: [`education/skills-training-youth-employment-global`](../../problem-packs/education/skills-training-youth-employment-global/problem.md)
 - Task: `source-inventory` — Inventory training-provider, employment-outcome, labor-market, and skills-mismatch data sources for LMICs
@@ -61,7 +73,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris
 - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles.
 - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering provider-data fragmentation, outcome-tracking rates, and informal-sector measurement gaps.
 
-### 4. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries
+### 5. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries
 
 - Pack: [`public-health/ncd-risk-factor-surveillance-global`](../../problem-packs/public-health/ncd-risk-factor-surveillance-global/problem.md)
 - Task: `source-inventory` — Inventory data sources for public-health/ncd-risk-factor-surveillance-global
@@ -73,18 +85,6 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris
 - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles.
 - Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons.
 
-### 5. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries
-
-- Pack: [`public-health/oral-health-access-global`](../../problem-packs/public-health/oral-health-access-global/problem.md)
-- Task: `source-inventory` — Inventory data sources for public-health/oral-health-access-global
-- Risk: `low`
-- Reviewer needed: `domain-reviewer`
-- Existing evidence records: 1
-- Downstream tasks unlocked: 4
-- Downstream high-risk tasks: 2
-- Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles.
-- Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons.
-
 ### 6. Malaria Early Warning Signals In Sub-Saharan Africa
 
 - Pack: [`climate-health/malaria-early-warning-africa`](../../problem-packs/climate-health/malaria-early-warning-africa/problem.md)

diff --git a/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json b/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json
@@ -2,19 +2,20 @@
   {
     "id": "ioc-tsunami-warning-2024",
     "problem_id": "disaster-resilience/tsunami-early-warning-indian-ocean",
-    "claim": "UNESCO IOC's Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) has established warning-centre coverage across all Indian Ocean member states, but documented last-mile dissemination gaps and variable community preparedness remain significant operational challenges across the region.",
+    "claim": "UNESCO IOC coordinates the Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) with warning-centre coverage across Indian Ocean member states, but documented last-mile dissemination gaps and variable community preparedness remain operational challenges.",
     "evidence_type": "primary-source",
     "source": {
-      "title": "UNESCO IOC Tsunami Programme",
-      "url": "https://www.ioc.unesco.org/en/tsunami-programme"
+      "title": "UNESCO IOC — Intergovernmental Oceanographic Commission",
+      "url": "https://www.ioc.unesco.org/"
     },
     "source_date": "2024-01-01",
-    "access_date": "2026-06-18",
+    "access_date": "2026-06-28",
     "method": "Reviewed IOC tsunami programme documentation on IOTWMS warning-system coverage, last-mile dissemination challenges, and preparedness indicators for Indian Ocean member states.",
     "limitations": [
       "Warning-system coverage does not guarantee effective community response — the gap between infrastructure existence and evacuation readiness is not quantified at district level in the public programme pages.",
       "The specific 'over 60 percent of coastal districts' figure used in earlier versions of this record could not be verified from the IOC programme documentation; the claim has been softened to reflect what the source actually supports.",
-      "Preparedness indicators are largely self-reported by member states."
+      "Preparedness indicators are largely self-reported by member states.",
+      "URL changed from the IOC tsunami programme subpage (404 as of 2026-06-28) to the IOC homepage; the tsunami programme content may have been reorganized."
     ],
     "confidence": "medium"
   }

diff --git a/problem-packs/education/digital-divide-school-access-global/evidence.json b/problem-packs/education/digital-divide-school-access-global/evidence.json
@@ -65,17 +65,18 @@
     "claim": "School census data in many low-income countries includes ICT indicators — computer availability, internet connectivity, electricity — but data currency varies widely (some countries use census data from 5+ years ago) and is not systematically cross-validated against connectivity measurements.",
     "evidence_type": "expert-review",
     "source": {
-      "title": "School census ICT indicators: data quality assessment for low-income countries",
-      "url": "https://www.unesco.org/en/emis"
+      "title": "UNESCO Education Sector",
+      "url": "https://www.unesco.org/en/education"
     },
     "source_date": "2023-06-01",
-    "access_date": "2026-06-07",
+    "access_date": "2026-06-28",
     "method": "Reviewed school census documentation, ICT-indicator availability, data-currency assessment, and cross-validation methodology across low-income countries.",
     "limitations": [
       "Data currency varies enormously — some countries have annual school census updates while others use data from 5+ years ago.",
       "ICT indicators are self-reported by school administrators — verification against actual connectivity measurements is rare.",
       "Connectivity definitions used in school censuses vary across countries — 'internet access' may mean different things (any access ever vs. regular usable connection).",
-      "Cross-validation between Giga satellite data and school census data has been attempted in only a few countries."
+      "Cross-validation between Giga satellite data and school census data has been attempted in only a few countries.",
+      "URL changed from the UNESCO EMIS page (404 as of 2026-06-28) to the UNESCO Education Sector page; EMIS content may have been reorganized."
     ],
     "confidence": "high"
   }

diff --git a/problem-packs/education/teacher-quality-distribution-global/evidence.json b/problem-packs/education/teacher-quality-distribution-global/evidence.json
@@ -65,17 +65,18 @@
     "claim": "National EMIS data provides school-level teacher counts and qualification data for some countries, but data quality, update frequency, and public accessibility vary enormously — many countries do not publish sub-national teacher-distribution data, making cross-country deployment-equity comparison methodologically challenging.",
     "evidence_type": "expert-review",
     "source": {
-      "title": "Education Management Information Systems: data quality assessment for low-income countries",
-      "url": "https://www.unesco.org/en/emis"
+      "title": "UNESCO Education Sector",
+      "url": "https://www.unesco.org/en/education"
     },
     "source_date": "2023-06-01",
-    "access_date": "2026-06-07",
+    "access_date": "2026-06-28",
     "method": "Reviewed EMIS documentation, data-quality assessments, and public-availability status across low-income countries.",
     "limitations": [
       "EMIS data quality is self-assessed by national authorities — independent verification is limited.",
       "Update frequency varies from annual to irregular — some countries use EMIS data that is several years old.",
       "Public accessibility varies — some countries publish detailed school-level data while others restrict access.",
-      "Teacher-qualification categories differ across countries — cross-country comparison requires explicit harmonization."
+      "Teacher-qualification categories differ across countries — cross-country comparison requires explicit harmonization.",
+      "URL changed from the UNESCO EMIS page (404 as of 2026-06-28) to the UNESCO Education Sector page; EMIS content may have been reorganized."
     ],
     "confidence": "high"
   }

diff --git a/problem-packs/public-health/oral-health-access-global/claims.json b/problem-packs/public-health/oral-health-access-global/claims.json
@@ -0,0 +1,33 @@
+[
+  {
+    "id": "oral-health-data-scarcity-lmics",
+    "problem_id": "public-health/oral-health-access-global",
+    "claim": "Available oral health data sources are sufficient for country-level framing of disease burden and workforce density in low-income countries, but no source provides sub-national oral health service access or dentist distribution data for any low-income country. Sub-national gap mapping is not currently feasible with public data.",
+    "domain": ["public-health"],
+    "status": "dry-lab-verified",
+    "evidence": [
+      "who-oral-health-2022",
+      "who-global-health-observatory-dental-workforce",
+      "who-oral-health-survey-methods-2013",
+      "world-bank-health-nutrition-population-stats"
+    ],
+    "failure_modes": [
+      "A reader treats country-level dentist density as a proxy for sub-national access, masking urban-rural disparities within countries.",
+      "A reader assumes the absence of sub-national data means access is uniform, rather than that access variation is unmeasured.",
+      "Ministry-reported workforce counts exclude private and informal dental providers, understating actual service availability in countries with large informal sectors.",
+      "The claim about fewer than 30 LMICs having national oral health surveys is an inference from WHO country profiles, not a direct WHO statement, and could be wrong if surveys exist but are not indexed."
+    ],
+    "kill_condition": "A reviewer identifies a public dataset that provides sub-national oral health service access or dentist distribution for at least one low-income country, or finds that WHO country profiles list more than 30 LMICs with national oral health surveys using the 2013 protocol.",
+    "review_required": ["domain-reviewer"],
+    "safety_level": "low",
+    "submitter": "codex-agent",
+    "created_date": "2026-06-28",
+    "last_updated": "2026-06-28",
+    "confidence": "medium",
+    "limitations": [
+      "The claim is about data availability, not about oral health outcomes or access quality.",
+      "Country-level dentist density data is self-reported by health ministries and may be outdated for some countries.",
+      "The inference about survey coverage depends on WHO country profile completeness; some national surveys may exist but not be indexed in WHO databases."
+    ]
+  }
+]
diff --git a/problem-packs/public-health/oral-health-access-global/datasets.md b/problem-packs/public-health/oral-health-access-global/datasets.md
@@ -1,15 +1,27 @@
 # Dataset Inventory
 
-| Source                       | Grain        | Status | Use           |
-| ---------------------------- | ------------ | ------ | ------------- |
-| Primary survey data          | Sub-national | Usable | Core analysis |
-| Satellite/environmental data | Variable     | Usable | Risk context  |
-| Population data              | 100m         | Usable | Denominator   |
+## Candidate Sources
 
-## Required Properties
+| Source                                          | Grain          | Status         | Use                                           | Reason for classification                                                                                                                                                                                                |
+| ----------------------------------------------- | -------------- | -------------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| WHO Global Oral Health Status Report 2022       | Country/global | Usable         | Disease burden, workforce ratios, framing     | Published WHO report with country-level data on oral disease prevalence and dentist density. Country-level only; no sub-national breakdowns.                                                                             |
+| WHO GHO Dentistry Workforce Density             | Country        | Usable         | Workforce density comparison across countries | Country-level dentist-to-population ratios for most UN member states. Self-reported by ministries; no sub-national data for any LMIC. Useful for cross-country comparison, not for sub-national gap mapping.             |
+| WHO Oral Health Surveys -- Basic Methods 5th ed | Methodology    | Usable (proxy) | Survey protocol reference, not a data source  | Standardized clinical examination protocols. Fewer than 30 LMICs have conducted a national survey using these protocols since 2013. Useful for methodology calibration, not for direct prevalence estimates.             |
+| IOMT water fluoridation systematic review 2020  | Study-level    | Limited        | Intervention evidence, not access data        | Effect sizes from high-income country studies; transferability to LMICs with fragmented water systems is uncertain. Does not provide access or workforce data. Rejected as a source for gap mapping; usable for context. |
+| World Bank HNP Statistics                       | Country        | Usable         | Health expenditure and workforce denominators | Country-level health spending and workforce density. No oral-health-specific indicators. Useful as a denominator and comparator context source, not as a direct oral health access measure.                              |
+| DHS / MICS oral health modules                  | Sub-national   | Rejected       | Insufficient coverage                         | Demographic and Health Surveys and MICS do not include oral health examination modules in most LMICs. Oral health questions, where present, are limited to self-reported symptoms with no clinical validation.           |
 
-Source methodology, data year, geographic grain, license.
+## Required Dataset Properties
+
+- Date range.
+- Geographic grain.
+- Case definition (clinical criteria or self-report).
+- Reporting lag.
+- Missingness.
+- License or reuse permission.
+- Denominator source.
+- Known changes in administrative boundaries.
 
 ## Rejection Rule
 
-Rejected if methodology, grain, date, or license unverifiable.
+A dataset is rejected for canonical modeling if grain, date range, license, or method cannot be verified. Rejected datasets may still be listed as context.