{
  "id": "AIBD-0230",
  "title": "Thorn's Spotlight matches a missing child's NCMEC photo to online sex ads; she may have been recovered within weeks",
  "summary": "In April 2019 a California officer ran a NCMEC missing-child photo through Thorn's Spotlight; Rekognition matching returned sex ads with the girl and, per Thorn's CEO, she was recovered within weeks.",
  "date_observed": "2019-06-19",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
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  "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.",
  "category": "benefit created",
  "unexpected": false,
  "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements.",
  "system": "Spotlight (Thorn), using Amazon Rekognition",
  "model_version": null,
  "developer": "Thorn (with Amazon Rekognition for face matching)",
  "deployer": "An unnamed California law enforcement officer and agency",
  "location": null,
  "domain": "Anti-trafficking / child protection",
  "segment": "Government",
  "benefit_type": "Reduced Violence",
  "taxonomy_note": "The recovery is reported only by the maker's CEO, and the AI's documented part was returning the ads.",
  "registry_ids": {},
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      "depth": 4,
      "reason": "A child sold for weeks was recovered and removed from trauma, per Thorn's CEO. No independent confirmation of the recovery is among the sources."
    }
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    "status": "assessed",
    "statement": "The face match that surfaced the ads is attributed to Amazon Rekognition inside Spotlight. The recovery itself came from conventional police work. Everything about this case rests on Thorn's CEO. Snopes documents that Thorn's aggregate figures derive from user surveys and were widely misreported."
  },
  "evidence": [
    {
      "kind": "news report",
      "citation": "Tom Simonite, WIRED, 19 Jun 2019",
      "title": "How Facial Recognition Is Fighting Child Sex Trafficking",
      "url": "https://www.wired.com/story/how-facial-recognition-fighting-child-sex-trafficking/",
      "date": "2019-06-19",
      "written_by": "independent",
      "quote": "Using Amazon’s facial recognition technology, Spotlight quickly returned a list of online sex ads featuring the girl’s photo."
    },
    {
      "kind": "other",
      "citation": "Dan MacGuill, Snopes fact check, 4 Sep 2018",
      "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?",
      "url": "https://www.snopes.com/fact-check/kutcher-software-child-trafficking/",
      "date": "2018-09-04",
      "written_by": "independent",
      "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked."
    }
  ],
  "replication": {
    "produced_by": [
      "A reference photo of the missing child",
      "An archive of scraped escort ads with faces indexed for similarity search",
      "An officer with Spotlight access who follows the matches with investigation"
    ],
    "must_hold": [
      "Ads with usable face images must exist for the victim",
      "Legal access to the ad archive and face matching",
      "Investigative capacity to act on matches quickly"
    ],
    "echoes": []
  },
  "paired_incident": null,
  "headline": "Spotlight may have led to a missing child's recovery in weeks",
  "metric": "claimed its tools helped identify 5,791 child victims and rescue 103",
  "comparator": null,
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    "status": "unknown",
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    "note": "No later development is established.",
    "quote": null,
    "url": null
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  "developer_country": "United States",
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  "unrated_because": null,
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      "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
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      "date": "2026-10-21",
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            "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.",
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          "kind": "legacy_record",
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          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "outcomes[].status": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].tradeoffs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].unexpected": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "unexpected": false,
            "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "unexpected",
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "places[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "developer_country": "United States"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "developer_country"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "purpose": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "record_dates": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "date_observed": "2019-06-19",
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
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              },
              {
                "date": "2026-10-21",
                "change": "Headline reworded to state the event without naming who claims it.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Title reworded to state the event without naming who claims it.",
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              },
              {
                "date": "2026-10-21",
                "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
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                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/Thorn_(organization)",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "replication.attempts[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "replication.conditions": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "replication": {
              "produced_by": [
                "A reference photo of the missing child",
                "An archive of scraped escort ads with faces indexed for similarity search",
                "An officer with Spotlight access who follows the matches with investigation"
              ],
              "must_hold": [
                "Ads with usable face images must exist for the victim",
                "Legal access to the ad archive and face matching",
                "Investigative capacity to act on matches quickly"
              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
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      "revision_history[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
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              },
              {
                "date": "2026-10-21",
                "change": "Headline reworded to state the event without naming who claims it.",
                "editor": "AIBD"
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              {
                "date": "2026-10-21",
                "change": "Title reworded to state the event without naming who claims it.",
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              {
                "date": "2026-10-21",
                "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
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                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/Thorn_(organization)",
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              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "revisions"
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sector": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "domain": "Anti-trafficking / child protection",
            "segment": "Government"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].access_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].citation_locator": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
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                "kind": "news report",
                "citation": "Tom Simonite, WIRED, 19 Jun 2019",
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                "date": "2019-06-19",
                "written_by": "independent",
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              },
              {
                "kind": "other",
                "citation": "Dan MacGuill, Snopes fact check, 4 Sep 2018",
                "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?",
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                "date": "2018-09-04",
                "written_by": "independent",
                "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked."
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            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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        },
        "review_state": "record_mapped",
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      },
      "sources[].id": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "AIBD-0230-source-0001",
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          "role": "Existing evidence items, in their original order"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Stable within the fingerprinted record version; no source content or source review has been added.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
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      "sources[].language": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
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                "kind": "news report",
                "citation": "Tom Simonite, WIRED, 19 Jun 2019",
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                "date": "2019-06-19",
                "written_by": "independent",
                "quote": "Using Amazon’s facial recognition technology, Spotlight quickly returned a list of online sex ads featuring the girl’s photo."
              },
              {
                "kind": "other",
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                "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?",
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                "date": "2018-09-04",
                "written_by": "independent",
                "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked."
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            ]
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        },
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          "record_fields": [
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].upstream_sources": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "strategic_assessments[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "strategic assessments"
      },
      "summary": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "summary": "In April 2019 a California officer ran a NCMEC missing-child photo through Thorn's Spotlight; Rekognition matching returned sex ads with the girl and, per Thorn's CEO, she was recovered within weeks.",
            "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources."
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        },
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          "source_refs": []
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        "review_state": "record_mapped",
        "coverage": "partial"
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      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "systems[].component_role": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "systems[].deployment_configuration": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "Spotlight (Thorn), using Amazon Rekognition"
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        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "Thorn (with Amazon Rekognition for face matching)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "Thorn's Spotlight matches a missing child's NCMEC photo to online sex ads; she may have been recovered within weeks",
            "headline": "Spotlight may have led to a missing child's recovery in weeks"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
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      "version": {
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          "role": "SHA-256 of normalized original case data"
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        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.",
            "replication": {
              "produced_by": [
                "A reference photo of the missing child",
                "An archive of scraped escort ads with faces indexed for similarity search",
                "An officer with Spotlight access who follows the matches with investigation"
              ],
              "must_hold": [
                "Ads with usable face images must exist for the victim",
                "Legal access to the ad archive and face matching",
                "Investigative capacity to act on matches quickly"
              ],
              "echoes": []
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          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 28,
      "reviewed": 0,
      "record_mapped": 28,
      "not_assessed": 63,
      "complete": false,
      "by_state": {
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        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 63,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}