{"id":"W2077517112","doi":"10.3354/meps11135","title":"Economic incentives and overfishing: a bioeconomic vulnerability index","year":2014,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Overfishing; Fishing; Fishery; Incentive; Geography; Vulnerability (computing); Population; Index (typography); Vulnerability index; Fisheries management; Ecology; Economics; Climate change; Biology; Demography; Sociology","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004528407,0.0001656806,0.0002440161,0.00003861589,0.0002097063,0.0001098835,0.0002610938,0.0001103616,0.01303901],"category_scores_gemma":[0.00007075779,0.0001584151,0.00003337308,0.00005312089,0.001429445,0.0005420418,0.001871658,0.0001972754,0.0001635556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001479084,"about_ca_system_score_gemma":0.00001692815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004694526,"about_ca_topic_score_gemma":0.00304883,"domain_scores_codex":[0.9986938,0.0001401029,0.0002251196,0.000473509,0.0000716116,0.0003958439],"domain_scores_gemma":[0.9994028,0.00009012672,0.00007941856,0.000300137,0.000005864624,0.0001216523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009187828,0.00004147022,0.9453327,0.00001483428,0.00001154644,0.000002407969,0.00006280556,0.000008559898,0.000007399507,0.0008129561,0.0004904997,0.05312296],"study_design_scores_gemma":[0.0003248551,0.0002440356,0.8857765,6.041856e-7,0.000004064057,0.00001858117,0.00003731603,0.0008550715,0.00007520506,0.003598627,0.1089024,0.0001628073],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9242549,0.000003897029,0.000002199239,0.001549222,0.0001394142,0.0002298984,0.000003235846,0.00005347852,0.07376379],"genre_scores_gemma":[0.996397,0.00003908973,0.0004598774,0.0001397032,0.00006878354,0.00009207909,0.00001226844,0.00001489727,0.002776278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1084119,"threshold_uncertainty_score":0.9878632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006454454180685025,"score_gpt":0.2340180808775225,"score_spread":0.2275636266968375,"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."}}