{"id":"W4362509219","doi":"10.1111/csp2.12926","title":"Application of <scp>AIS</scp> ‐ and flyover‐based methods to monitor illegal and legal fishing in Canada's Pacific marine conservation areas","year":2023,"lang":"en","type":"article","venue":"Conservation Science and Practice","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada","keywords":"Fishing; Marine conservation; Automatic Identification System; Fishery; Marine protected area; Identification (biology); Environmental resource management; Geography; Computer science; Environmental science; Computer security; Ecology; Habitat","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003120027,0.0001102342,0.0001583902,0.00009534745,0.000257174,0.0001022646,0.0001384484,0.00002983138,0.00001363446],"category_scores_gemma":[0.006865053,0.0001106567,0.000007436648,0.001683635,0.0002863347,0.001178669,0.0004017369,0.00009891963,0.000004796794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002051854,"about_ca_system_score_gemma":0.0002171419,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.760987,"about_ca_topic_score_gemma":0.4748163,"domain_scores_codex":[0.9984563,0.0001590351,0.00027545,0.0004034085,0.0004865513,0.0002192424],"domain_scores_gemma":[0.9971927,0.002208103,0.0001938679,0.0001668299,0.000115914,0.0001225549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003495282,0.00001944573,0.8900687,0.0000461274,0.000004619496,0.000005818752,0.0003471072,0.00007297363,0.009472257,0.0005057512,0.003734817,0.09568748],"study_design_scores_gemma":[0.0001756331,0.00003544119,0.858911,0.00001114193,0.00001043351,0.000009007681,0.001454349,0.02502181,0.0006699953,0.00006259483,0.1135803,0.00005822833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795613,0.00003916622,0.0009133499,0.01358063,0.00005596751,0.0003782621,0.000005708235,0.00001741547,0.005448201],"genre_scores_gemma":[0.9855198,0.0001524165,0.01052981,0.00361881,0.00001195754,0.00004695094,0.000005322312,0.000006500425,0.000108397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2861706,"threshold_uncertainty_score":0.8218605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03505730215573743,"score_gpt":0.3190614691131259,"score_spread":0.2840041669573884,"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."}}