{"id":"W2156523992","doi":"10.1126/science.1173146","title":"Rebuilding Global Fisheries","year":2009,"lang":"en","type":"article","venue":"Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":2199,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Fisheries management; Fishery; Marine ecosystem; Ecosystem; Fisheries law; Marine fisheries; Fisheries science; Scale (ratio); Environmental resource management; Business; Geography; Ecology; Environmental science; Fish <Actinopterygii>; Fishing; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000976958,0.0007312371,0.0003461996,0.001181444,0.0007895931,0.00245063,0.0005815875,0.0007453561,0.01182364],"category_scores_gemma":[0.001452441,0.0001180087,0.0003920533,0.001687837,0.001102238,0.004617458,0.003011992,0.0007675228,0.001722151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008320981,"about_ca_system_score_gemma":0.0018577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003980451,"about_ca_topic_score_gemma":0.01113174,"domain_scores_codex":[0.9996642,0.00005308345,0.00001881355,0.000071239,0.0000852894,0.0001073928],"domain_scores_gemma":[0.9993642,0.00007007892,0.00009427247,0.0001451895,0.0002059748,0.0001203227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008014114,0.00007043735,0.03870141,0.0007522969,0.0001469235,0.0006646459,0.001908654,0.002748577,0.009057919,0.06907117,0.03914157,0.8376563],"study_design_scores_gemma":[0.000009998402,0.0001684216,0.08145554,0.0006575935,0.00009278817,0.0008893128,0.006261386,0.001167475,0.002632069,0.0413812,0.8652539,0.00003035615],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4706123,0.05614154,0.02768758,0.050473,0.002168576,0.0001606259,0.001518727,0.001068669,0.390169],"genre_scores_gemma":[0.8720356,0.04979832,0.01997467,0.009950722,0.0006859672,0.00008738077,0.001284923,0.0002232517,0.04595922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01182364,"threshold_uncertainty_score":0.03955406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01404749740193564,"score_gpt":0.2739718931459585,"score_spread":0.2599243957440229,"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."}}