[
 {
  "id": "CAP-1-01",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the composition gives the monitor's input as its methodology page does: Event Registry and the 150,000 articles a day",
  "kind": "fact",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[0] s1–2",
  "quote": "THE PIPELINE'S INPUT RIGHT, ITS MACHINE UNSAID. Event Registry and the 150,000 articles a day are the methodology page's.",
  "kernel": false,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19211770,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-02",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the composition does not say that LLMs have classified the events since November 2024 and written their titles and summaries",
  "kind": "fact",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[0] s3",
  "quote": "That large language models have classified the events since November 2024 and written their titles and summaries (GPT-4o mini, GPT-4o, o3-mini) is not said.",
  "kernel": true,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19211892,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
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 {
  "id": "CAP-1-03",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "two readings of the entity: the MMRS record's machine reception of the news against the composition's aggregator of the news",
  "kind": "interpretation",
  "modality": "interpretation",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[0] s4",
  "quote": "The record reads the monitor as itself a machine reception of the news; the composition reads it as an aggregator of the news.",
  "kernel": false,
  "const": false,
  "lineage": "the monitor as machine reception",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19212049,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-04",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the finding's basis: the MMRS record and the entity's own pages, re-read 2026-10-29",
  "kind": "fact",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[0] s5",
  "quote": "Checked 2026-10-29 against the MMRS meta-aggregator record of 2026-10-28 and the entity's own pages, re-read the same day.",
  "kernel": false,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 18935124,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-05",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the composition's maker ('developed by the OECD.AI Policy Observatory in collaboration with') is close to the methodology page's expert group with McGovern support",
  "kind": "interpretation",
  "modality": "interpretation",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[1]",
  "quote": "THE MAKER. The methodology page says the monitor 'was initiated and is being developed by the OECD.AI expert group on AI incidents' with support from the Patrick J. McGovern Foundation; 'developed by the OECD.AI Policy Observatory in collaboration with' is close.",
  "kernel": false,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19212306,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-06",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the composition's fourteen themes come from a card, the 2026 trends paper; the methodology page gives no count; not verified by the record",
  "kind": "limit",
  "modality": "self-description",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, findings[2]",
  "quote": "FOURTEEN THEMES. The count comes from a card ('Trends in AI incidents and hazards reported by the media'); the methodology page read gives no count of themes. Not verified here.",
  "kernel": false,
  "const": false,
  "lineage": "themes: the 2026 paper's analysis",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field findings",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19212577,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-07",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the composition gives the monitor's inputs and definitions right and leaves out its classifier, which makes each record a machine composition",
  "kind": "interpretation",
  "modality": "interpretation",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, analysis s1",
  "quote": "The monitor is composed from its own methodology page with its inputs and definitions right and its classifier left out, the part of its method that makes each record a machine composition.",
  "kernel": true,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field analysis",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19209014,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "CAP-1-08",
  "dep": "capture:oecd-ai-incidents-and-hazards-monitor-aio-20261029",
  "record": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/",
   "label": "Capture Registry, 2026-10-29"
  },
  "claim": "the MMRS record holds what the composition drops",
  "kind": "interpretation",
  "modality": "interpretation",
  "strata": [
   "D"
  ],
  "locus": "oecd-ai-incidents-and-hazards-monitor-aio-20261029, analysis s2",
  "quote": "The record holds what the composition drops.",
  "kernel": false,
  "const": false,
  "lineage": "reception: the composition layer",
  "date": "2026-10-29",
  "title": "Capture Registry observation OBS-23f50c1b7e04 (oecd-ai-incidents-and-hazards-monitor-aio-20261029), field analysis",
  "creator": "Capture Registry (Lee Sharks, operator)",
  "file": "data/EA-WG-CAPTURES-01.json",
  "offset": 19209204,
  "quote_ok": true,
  "quote_check": "verbatim within the field's value as loaded",
  "surface": {
   "url": "https://www.alexanarch.org/captures/oecd-ai-incidents-and-hazards-monitor-aio-20261029/"
  }
 },
 {
  "id": "MMRS-01",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "what it is: an automated monitor of AI harm events in the news, run by OECD.AI",
  "kind": "definition",
  "modality": "stipulation",
  "strata": [
   "D"
  ],
  "locus": "articles.py ARTICLES['oecd-ai-incidents-monitor'], kernel s1",
  "quote": "The OECD AI Incidents and Hazards Monitor (AIM) is an automated monitor of AI harm events in the news, run by OECD.AI.",
  "kernel": true,
  "const": false,
  "lineage": "what it is: an automated media monitor",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 5305,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-02",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "how: AI-tagged news events from Event Registry daily; since November 2024 LLMs sort them and write their summaries; about 18,579 listed",
  "kind": "function",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, kernel s2",
  "quote": "It reads AI-tagged news events from Event Registry daily and, since November 2024, has large language models sort them into incidents and hazards and write their summaries; about 18,579 are listed.",
  "kernel": false,
  "const": false,
  "lineage": "method: LLM classification since November 2024",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 5424,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-03",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "the monitor's self-description, quoted",
  "kind": "attribution",
  "modality": "attributed",
  "strata": [
   "D"
  ],
  "locus": "articles.py, What it is s1",
  "quote": "The monitor calls itself an \"Automated media discourse monitor of AI incidents and hazards (Beta).\"",
  "kernel": false,
  "const": false,
  "lineage": "what it is: an automated media monitor",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 5658,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-04",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "the unit's two terms, in the OECD's definitions",
  "kind": "definition",
  "modality": "attributed",
  "strata": [
   "D"
  ],
  "locus": "articles.py, What it is s2",
  "quote": "An AI incident is an event in which the development, use or malfunction of an AI system directly or indirectly leads to harm; an AI hazard is an event that \"could plausibly lead to an AI incident.\"",
  "kernel": false,
  "const": false,
  "lineage": "definitions: incident and hazard",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 5760,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-05",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "the definitions' source: the OECD paper of May 2024",
  "kind": "attribution",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, What it is s3",
  "quote": "The definitions follow the OECD's paper of May 2024.",
  "kernel": false,
  "const": false,
  "lineage": "definitions: incident and hazard",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 5960,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-06",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "intake: Event Registry's clusters; only AI-tagged events reach the monitor",
  "kind": "function",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, How it works s1",
  "quote": "Event Registry clusters news articles about one happening into an event, and only events tagged with AI concepts reach the monitor.",
  "kernel": false,
  "const": false,
  "lineage": "intake: Event Registry's news events",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 6038,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-07",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "the pipeline's models: GPT-4o mini filters, GPT-4o reclassifies, o3-mini writes the record from the top three articles",
  "kind": "function",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, How it works s2",
  "quote": "Since November 2024 a small model (GPT-4o mini) filters, a larger one (GPT-4o) reclassifies, and o3-mini writes the title, summary, harm type, severity, stakeholders and country from the top three articles.",
  "kernel": false,
  "const": false,
  "lineage": "method: LLM classification since November 2024",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 6170,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-08",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "grouping by embedding similarity",
  "kind": "function",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, How it works s3",
  "quote": "New items are matched to existing events by embedding similarity.",
  "kernel": false,
  "const": false,
  "lineage": "method: LLM classification since November 2024",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 6377,
  "quote_ok": true,
  "quote_check": "within the ARTICLES value as loaded from articles.py (whitespace-normalised)",
  "entity": "oecd-ai-incidents-monitor",
  "surface": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/"
  }
 },
 {
  "id": "MMRS-09",
  "dep": "MMRS",
  "record": {
   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
   "label": "MMRS"
  },
  "claim": "cadence: daily, on events one to four days old",
  "kind": "function",
  "modality": "documented",
  "strata": [
   "D"
  ],
  "locus": "articles.py, How it works s4",
  "quote": "The pipeline runs daily on events one to four days old.",
  "kernel": false,
  "const": false,
  "lineage": "cadence: daily, one to four days",
  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
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  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
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   "O"
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
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  "const": false,
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 6861,
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 {
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   "label": "MMRS"
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  "kernel": false,
  "const": false,
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 6961,
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 {
  "id": "MMRS-15",
  "dep": "MMRS",
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   "label": "MMRS"
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   "D"
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  "kernel": false,
  "const": false,
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: ai-incident-database (https://www.machinemediation.org/aggregators/ai-incident-database/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 2399,
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 {
  "id": "MMRS-16",
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  "const": false,
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: aiaaic-repository (https://www.machinemediation.org/aggregators/aiaaic-repository/), editor Lee Sharks",
  "creator": "Lee Sharks (editor)",
  "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py",
  "offset": 8157,
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   "url": "https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/",
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  "const": false,
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  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
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  "kernel": false,
  "const": false,
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
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  "date": "2026-10-28 (corrected 2026-10-29)",
  "title": "MMRS meta-aggregator record: OECD AI Incidents and Hazards Monitor (https://www.machinemediation.org/aggregators/oecd-ai-incidents-monitor/), editor Lee Sharks",
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 {
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]