{"id":"W1968413785","doi":"10.1139/f04-084","title":"A Bayesian hierarchical formulation of the De Lury stock assessment model for abundance estimation of Falkland Islands' squid (<i>Loligo gahi</i>)","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Cephalopods and Marine Biology","field":"Agricultural and Biological Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nuffield Foundation","keywords":"Stock assessment; Fishery; Fishing; Stock (firearms); Loligo; Bayesian probability; Environmental science; Abundance (ecology); Oceanography; Econometrics; Squid; Ecology; Statistics; Biology; Geography; Mathematics; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003885729,0.00005958218,0.0001449079,0.00002162229,0.0002221183,0.00003579594,0.0001787066,0.00003913947,0.00001041229],"category_scores_gemma":[0.0001075914,0.00002196166,0.00006129249,0.0001456789,0.000296385,0.0001266404,0.00001193477,0.00005087093,1.858256e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002937471,"about_ca_system_score_gemma":0.0003514001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002185419,"about_ca_topic_score_gemma":0.03673984,"domain_scores_codex":[0.9993727,0.00002358709,0.0002543371,0.00007904382,0.0001129245,0.0001573749],"domain_scores_gemma":[0.9994918,0.0001071918,0.0002228777,0.0000254282,0.00004373539,0.0001089893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001459743,0.0001308635,0.5450135,0.0001242413,0.000064083,0.000004096427,0.005596443,0.01979459,0.02805345,0.02346935,0.0004583444,0.3771451],"study_design_scores_gemma":[0.0006865757,0.001854641,0.4742711,0.0001541049,0.00004345393,0.00006907785,0.001013298,0.4084483,0.0007562239,0.1118127,0.0007004141,0.0001900459],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836373,0.00008187495,0.01273773,0.003187794,0.00006894046,0.0001105486,0.00001399201,9.821092e-7,0.0001608147],"genre_scores_gemma":[0.9938847,0.00001610013,0.005929921,0.0001059351,0.00003798481,0.00000217687,0.000001915465,4.381455e-7,0.00002082688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3886537,"threshold_uncertainty_score":0.9808372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820180746405108,"score_gpt":0.2426395802848096,"score_spread":0.2244377728207585,"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."}}