{"id":"W4388076380","doi":"10.3897/aiep.53.105910","title":"New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method","year":2023,"lang":"en","type":"article","venue":"Acta Ichthyologica Et Piscatoria","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University; University of British Columbia","funders":"Horizon 2020 Framework Programme; Minderoo Foundation; European Commission","keywords":"Stock assessment; Stock (firearms); Prior probability; Econometrics; Fishery; Bayesian probability; Statistics; Computer science; Fish stock; Environmental science; Mathematics; Fish <Actinopterygii>; Fishing; Geography; Biology","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":[0.004955246,0.001403618,0.001265351,0.003128548,0.0004373219,0.001946962,0.001644622,0.0007391467,0.004161143],"category_scores_gemma":[0.01535684,0.0006633511,0.00184677,0.003980317,0.0006371418,0.002150933,0.002926316,0.002282303,0.001871576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000654395,"about_ca_system_score_gemma":0.001563318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007123506,"about_ca_topic_score_gemma":0.005698356,"domain_scores_codex":[0.9960348,0.001174623,0.0003531226,0.0008158246,0.001532929,0.0000887312],"domain_scores_gemma":[0.9940495,0.002701847,0.0008143461,0.001043396,0.001229336,0.0001616283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001810278,0.00008817206,0.03080913,0.0007045899,0.0008232923,0.0002490631,0.000232116,0.09827473,0.006336397,0.06980643,0.02104087,0.7714541],"study_design_scores_gemma":[0.00003817295,0.0001410763,0.02204245,0.0002371434,0.0001650112,0.000381587,0.00009977559,0.8361821,0.003411115,0.05527864,0.08184394,0.000178937],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006508715,0.001107687,0.9876132,0.0004134191,0.0002567034,0.00006395961,0.001273052,0.0007004424,0.002062755],"genre_scores_gemma":[0.09967801,0.002570102,0.8838573,0.0004947548,0.000881197,0.0004075209,0.004410557,0.0009551958,0.006745415],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007123506,"threshold_uncertainty_score":0.02620614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04024696437711011,"score_gpt":0.3622406730895673,"score_spread":0.3219937087124572,"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."}}