{"id":"W4300062807","doi":"","title":"Embedding Atlantic salmon population dynamics and stock assessment within a hierarchical bayesian integrated life cycle modelling framework","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Bayesian probability; Embedding; Computer science; Population; Econometrics; Artificial intelligence; Mathematics; Demography","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":[0.00231702,0.000601099,0.001136894,0.0006806332,0.0004359731,0.001561617,0.002069998,0.001781772,0.0021474],"category_scores_gemma":[0.00810042,0.001172903,0.0015321,0.0007493375,0.0009504188,0.001986857,0.001620139,0.001401859,0.0003352494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378067,"about_ca_system_score_gemma":0.001924094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03878316,"about_ca_topic_score_gemma":0.03657436,"domain_scores_codex":[0.9992448,0.0003797093,0.00004815916,0.0001602008,0.00009956299,0.00006760505],"domain_scores_gemma":[0.9972062,0.001899961,0.000315603,0.0001572906,0.0002710635,0.0001499258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001341817,0.000009749412,0.0004277453,0.000008431299,0.00002339587,0.0000115212,0.00001660255,0.9934828,0.0001295459,0.003366476,0.00004755784,0.002462758],"study_design_scores_gemma":[0.000001642221,0.000002911433,0.00007256529,0.000001528583,0.000003731803,0.000001502859,0.000001704633,0.9979984,0.00002044014,0.001861939,0.00003162937,0.000001977646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07904484,0.0001699518,0.9186348,0.0003589681,0.00002616596,0.0000374407,0.0002366461,0.0002006714,0.001290548],"genre_scores_gemma":[0.861428,0.0002423168,0.1338599,0.0001218495,0.00005409155,0.0001272059,0.0005390909,0.0001083787,0.003519237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03878316,"threshold_uncertainty_score":0.07711482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276003832832088,"score_gpt":0.2589816402720844,"score_spread":0.2462216019437635,"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."}}