{
  "id": "AIBD-0362",
  "title": "Rapiscan and Taronga/Macquarie CT algorithms detect shark fins, seahorses, and sea cucumbers at 86–96% in laboratory testing",
  "summary": "A vendor-affiliated CT study reported 86–96% detection of three marine-wildlife classes and 13% overall false alarms; testing used original scans and synthetic composites, with no customs outcome.",
  "date_observed": "2026-06-08",
  "date_basis": "source publication",
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  "account": "Pirotta and colleagues tested AI detection of marine wildlife in three-dimensional X-ray scans. Their June 8, 2026 paper reports 298 scans from 68 specimens, including preserved specimens and fresh shark material. The researchers expanded the scans by inserting specimen images into baggage images. A 512-bag test set contained both original scans and these synthetic composites, drawn from the same specimen population. Table 3 reports detection rates of 95% for shark fins, 96% for seahorses, and 86% for sea cucumbers. The overall false-alarm rate was 13%; the class-specific rates were 2%, 9%, and 1%. Rapiscan supplied equipment and funded staff participation in analysis and writing. The paper demonstrates laboratory detection, with no reported operational seizure or customs evaluation.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Automated detection of marine wildlife in CT scans of mail and luggage to support customs inspection; no operational evaluation is reported.",
  "system": "Rapiscan 3D X-ray CT marine-wildlife detection algorithms (3D convolutional neural networks with 3D Threat Image Projection)",
  "model_version": "Experimental 3D convolutional neural networks trained on CT scans and synthetic Threat Image Projection composites; no released model version reported",
  "developer": "Rapiscan Systems Ltd with Taronga Conservation Society Australia and Macquarie University",
  "deployer": "None; proof of concept with no customs authority deployment",
  "location": "Sydney, New South Wales, Australia (research setting)",
  "domain": "Wildlife trafficking detection at borders",
  "segment": "Security-screening vendor and conservation research partnership",
  "benefit_type": "Improved Task Accuracy",
  "taxonomy_note": "Lab detection rates for trafficked wildlife are read as task performance; no seizure is documented.",
  "registry_ids": {},
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      "reason": "Laboratory detection rates only."
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    "statement": "AI classified objects in CT baggage scans. Most positive test bags used synthetically inserted specimens, and testing drew from the same specimen population. The paper is original research with disclosed Rapiscan involvement, not an independent deployment evaluation."
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  "evidence": [
    {
      "kind": "peer-reviewed study",
      "citation": "Pirotta, V., Meagher, P., Phan, H. T. H., Shen, K., Thompson, W., Dolman, B., Bending, Z., Smoothey, A. F., Hay, A., Rowe, C. E., Motamayor, A., Liddell, B., Allende, A., Allman, B. E., O'Brien, J. K. (2026). Marine wildlife trafficking: use of AI algorithms for the autodetection of shark fins, seahorses and sea cucumbers. Frontiers in Ocean Sustainability. doi:10.3389/focsu.2026.1776978; §§2–3, tables 1–3, data availability, and conflict-of-interest statement.",
      "title": "Marine wildlife trafficking: use of AI algorithms for the autodetection of shark fins, seahorses and sea cucumbers",
      "url": "https://www.frontiersin.org/journals/ocean-sustainability/articles/10.3389/focsu.2026.1776978/full",
      "date": "2026-06-08",
      "written_by": "makers",
      "quote": null
    }
  ],
  "replication": {
    "produced_by": [
      "Rapiscan 3D X-ray CT scanners already used for security screening",
      "Preserved marine specimens and fresh shark material scanned with the Rapiscan RTT110",
      "Synthetic data expansion with 3D Threat Image Projection",
      "Vendor funding of the research"
    ],
    "must_hold": [
      "Access to CT scanners at mail and airport screening points",
      "Algorithm performance on concealed, mixed consignments",
      "Customs authority adoption",
      "Legal basis for seizure on algorithm alerts"
    ],
    "echoes": []
  },
  "paired_incident": null,
  "headline": "Rapiscan CT algorithms detect marine wildlife at 86–96% in testing",
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    "against": "known scanned samples (ground truth), not human inspectors",
    "before": null,
    "after": "PD shark fin: 95%, seahorse: 96% and sea cucumber: 86%",
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    "quote": "The performance of the detection algorithm across all marine species subclasses was high (Table 3, PD shark fin: 95%, seahorse: 96% and sea cucumber: 86%), with low false alarm rates (PFA shark fin: 2%, seahorse: 9% and sea cucumber: 1%).",
    "url": "https://www.frontiersin.org/articles/10.3389/focsu.2026.1776978/full"
  },
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    "note": "The authors say implementation at the front lines is the next step; no customs trial or deployment of the algorithms is reported in the cited sources.",
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      "change": "Added what the benefit is measured against from the cited sources.",
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      "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.",
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      "source": "https://find-and-update.company-information.service.gov.uk/company/02755398",
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          "basis": "Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications. Access limits are enumerated in the review.",
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        "review_state": "reviewed",
        "coverage": "complete",
        "display": {
          "answer": "The final paper supplies the detection rates in table 3. Its supplement was inaccessible, and raw data require permission. The training total in § 3.1 appears inconsistent with the listed class counts.",
          "editor_note": ""
        }
      },
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          "text": "Researchers trained the networks on CT scans and synthetic images with inserted marine-wildlife specimens."
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          "source_refs": []
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        },
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        "review_state": "record_mapped",
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        "value": {
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        "provenance": {
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          "source_refs": []
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        "review_state": "record_mapped",
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        "provenance": {
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        "display": {
          "answer": "The experimental convolutional networks have no published release identifier.",
          "editor_note": ""
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        "value": {
          "kind": "record_fields",
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          "record_fields": [
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          ],
          "source_refs": []
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        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
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        "review_state": "not_assessed",
        "coverage": "partial"
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        "value": {
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          "fields": {
            "title": "Rapiscan and Taronga/Macquarie CT algorithms detect shark fins, seahorses, and sea cucumbers at 86–96% in laboratory testing",
            "headline": "Rapiscan CT algorithms detect marine wildlife at 86–96% in testing"
          }
        },
        "provenance": {
          "kind": "source_review",
          "basis": "Updated the mapped fields during the source review. Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.",
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        "coverage": "complete"
      },
      "workflow": {
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        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Pirotta and colleagues tested AI detection of marine wildlife in three-dimensional X-ray scans. Their June 8, 2026 paper reports 298 scans from 68 specimens, including preserved specimens and fresh shark material. The researchers expanded the scans by inserting specimen images into baggage images. A 512-bag test set contained both original scans and these synthetic composites, drawn from the same specimen population. Table 3 reports detection rates of 95% for shark fins, 96% for seahorses, and 86% for sea cucumbers. The overall false-alarm rate was 13%; the class-specific rates were 2%, 9%, and 1%. Rapiscan supplied equipment and funded staff participation in analysis and writing. The paper demonstrates laboratory detection, with no reported operational seizure or customs evaluation.",
            "replication": {
              "produced_by": [
                "Rapiscan 3D X-ray CT scanners already used for security screening",
                "Preserved marine specimens and fresh shark material scanned with the Rapiscan RTT110",
                "Synthetic data expansion with 3D Threat Image Projection",
                "Vendor funding of the research"
              ],
              "must_hold": [
                "Access to CT scanners at mail and airport screening points",
                "Algorithm performance on concealed, mixed consignments",
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                "Legal basis for seizure on algorithm alerts"
              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "source_review",
          "basis": "Updated the mapped fields during the source review. Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.",
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        },
        "review_state": "reviewed",
        "coverage": "partial",
        "display": {
          "answer": "Researchers scanned marine specimens with a Rapiscan RTT110. They inserted specimens digitally into other CT images to expand the training data and then tested the detection algorithms.",
          "editor_note": ""
        }
      }
    },
    "summary": {
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      "addressed": 91,
      "known": 34,
      "reviewed": 20,
      "record_mapped": 14,
      "not_assessed": 57,
      "complete": false,
      "by_state": {
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        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 57,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}