{"id":"W2123908016","doi":"10.1139/f07-024","title":"A Bayesian hierarchical meta-analysis of growth for the genus<i>Sebastes</i>in the eastern Pacific Ocean","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sebastes; Bayesian probability; Stock assessment; Covariate; Biology; Statistics; Bayesian hierarchical modeling; Prior probability; Population; Ecology; Mathematics; Bayesian inference; Fishery; Fish <Actinopterygii>; Demography; Fishing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02254662,0.00164295,0.00371677,0.006000563,0.001051969,0.001800752,0.001382851,0.001140799,0.001362477],"category_scores_gemma":[0.01971859,0.000972891,0.01162585,0.004560123,0.0008247893,0.0009860942,0.001084447,0.001071227,0.0001108235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108513,"about_ca_system_score_gemma":0.001911858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01310217,"about_ca_topic_score_gemma":0.02329201,"domain_scores_codex":[0.9907905,0.006195337,0.0006256186,0.001547159,0.0006741336,0.0001672251],"domain_scores_gemma":[0.9833423,0.01300889,0.001091654,0.001624576,0.0006491503,0.0002833385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.003271292,0.0001209666,0.1929489,0.008302952,0.7122716,0.0004745703,0.0004214034,0.03037787,0.006415629,0.001062056,0.001187008,0.04314584],"study_design_scores_gemma":[0.001116917,0.0009697127,0.1822748,0.001426904,0.7516582,0.0003376822,0.0003761288,0.05172275,0.002247449,0.00437994,0.003323726,0.0001656959],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8251747,0.1260428,0.04255497,0.001252432,0.0002914829,0.0002066529,0.00289862,0.0006472077,0.0009311747],"genre_scores_gemma":[0.9740852,0.006335219,0.01805181,0.0001272447,0.00004191018,0.0001392036,0.0009523143,0.0000653744,0.0002017864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02254662,"threshold_uncertainty_score":0.1192393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04607061121147771,"score_gpt":0.2611096678580978,"score_spread":0.2150390566466201,"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."}}