{"id":"W4414011120","doi":"10.1126/sciadv.ads1592","title":"Leveraging port state measures to combat illegal, unreported, and unregulated fishing","year":2025,"lang":"en","type":"article","venue":"Science Advances","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fishing; Port (circuit theory); State (computer science); Business; Computer science; Computer security; Fishery; Engineering; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004037621,0.0003091859,0.0001977129,0.001280506,0.001204119,0.00203874,0.0008435433,0.0006190877,0.0050299],"category_scores_gemma":[0.01377653,0.0001465827,0.0003989848,0.0009223563,0.001164156,0.002803736,0.002677907,0.001227656,0.0005290008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378965,"about_ca_system_score_gemma":0.004942819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01066027,"about_ca_topic_score_gemma":0.02548148,"domain_scores_codex":[0.997563,0.001018035,0.0001392066,0.0002292724,0.000563303,0.0004870889],"domain_scores_gemma":[0.992193,0.001786301,0.00245154,0.001003754,0.001510221,0.001055134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002641969,0.0009204666,0.5206898,0.0005175892,0.0002343002,0.0007995765,0.004254804,0.009098192,0.008568184,0.03027413,0.01193069,0.4124482],"study_design_scores_gemma":[0.00005285723,0.001776639,0.7923166,0.001262416,0.0002661271,0.0006505591,0.01840154,0.02004967,0.01010452,0.02075114,0.1341923,0.0001756341],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8848242,0.0008140338,0.02820688,0.004496817,0.0003608523,0.0004626723,0.0005556472,0.0006314715,0.07964735],"genre_scores_gemma":[0.9898949,0.0002585046,0.006289025,0.000447079,0.0000418783,0.0001178445,0.0001925243,0.00003106038,0.002727261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01066027,"threshold_uncertainty_score":0.02135324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655932080752336,"score_gpt":0.2876104275288578,"score_spread":0.2710511067213344,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}