{"id":"W200176590","doi":"10.1111/j.1752-4571.2009.00077.x","title":"ORIGINAL ARTICLE: Implications of fisheries‐induced evolution for stock rebuilding and recovery","year":2009,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":238,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry","funders":"Bergens Forskningsstiftelse; Academy of Finland; Norges Forskningsråd; Austrian Science Fund; European Science Foundation; European Commission","keywords":"Biology; Gadus; Fishing; Fisheries management; Fish stock; Fishery; Preharvest; Stock (firearms); Atlantic cod; Ecology; Fish <Actinopterygii>; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001479112,0.00009088673,0.0001047931,0.0000466819,0.0003263112,0.00001546856,0.000168301,0.00006168258,0.0006482239],"category_scores_gemma":[0.00004568261,0.00009774025,0.00004548396,0.0004202243,0.0001371201,0.0003068449,0.00007344018,0.00008797326,0.00002202138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001868499,"about_ca_system_score_gemma":0.00003641973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009165511,"about_ca_topic_score_gemma":0.00002264745,"domain_scores_codex":[0.9990854,0.00002168413,0.0002313565,0.0002894883,0.0001526146,0.0002195024],"domain_scores_gemma":[0.9993739,0.00009010442,0.00007988622,0.0003203071,0.00004233982,0.00009348431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000178569,0.0006076411,0.4426988,0.00003725852,0.00003200275,3.691881e-7,0.0001111685,0.0002477063,0.1174242,0.139714,0.04049664,0.2584516],"study_design_scores_gemma":[0.0002531057,0.0002172044,0.8210467,0.000002977572,0.00001601991,0.00001583583,0.00003452673,0.002220439,0.0002494971,0.06357758,0.1122149,0.0001512718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5085458,0.0001207609,0.342104,0.01357233,0.00006017758,0.003371743,0.0001785921,0.0001792886,0.1318674],"genre_scores_gemma":[0.9795144,0.00003702872,0.01856809,0.00009794004,0.00007310598,0.0006352356,0.00004836167,0.000008973088,0.001016849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4709687,"threshold_uncertainty_score":0.7097597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948301707704449,"score_gpt":0.2760281054302371,"score_spread":0.2565450883531927,"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."}}