{"id":"W2022365614","doi":"10.1073/pnas.1212593110","title":"Economic repercussions of fisheries-induced evolution","year":2013,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry","funders":"Universitetet i Oslo; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Vienna Science and Technology Fund; Norges Forskningsråd; Austrian Science Fund; European Science Foundation; European Commission","keywords":"Fishing; Fish stock; Stock (firearms); Biology; Productivity; Phenotypic plasticity; Economics; Fisheries management; Fishery; Ecology; Geography","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":[0.001106647,0.0002665978,0.0002358525,0.0003946719,0.0003960395,0.0008925833,0.0003473016,0.0006064013,0.002058567],"category_scores_gemma":[0.005431274,0.000201021,0.0005069043,0.0003611675,0.000687532,0.0006244143,0.0007898558,0.0005011511,0.0001137608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008675965,"about_ca_system_score_gemma":0.0003743653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001939585,"about_ca_topic_score_gemma":0.003363344,"domain_scores_codex":[0.9996743,0.0001547761,0.00002567669,0.00004735272,0.00003660056,0.00006140796],"domain_scores_gemma":[0.9986857,0.0006636704,0.0002845186,0.0001659804,0.00008761519,0.0001125329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007023819,0.0003967246,0.614743,0.0001311331,0.0006675011,0.001956603,0.0002631291,0.2829723,0.03021997,0.03840192,0.000867893,0.02867737],"study_design_scores_gemma":[0.00005836381,0.0002993199,0.7512245,0.00002170116,0.0001726534,0.0005749977,0.0003260612,0.2180945,0.002216804,0.02574919,0.001186375,0.00007547517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967601,0.00008064975,0.0009941411,0.0001805137,0.000005283435,0.0000032061,0.00008753913,0.00001009577,0.001878615],"genre_scores_gemma":[0.9993408,0.00005415065,0.0002749239,0.00003126587,0.000003227723,0.000003713082,0.00005447147,0.000005495425,0.000231993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002058567,"threshold_uncertainty_score":0.006886601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03633424888331391,"score_gpt":0.2814778056104756,"score_spread":0.2451435567271617,"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."}}