{"id":"W2344281158","doi":"10.1890/14-2379","title":"Stochastic life history modeling for managing regional‐scale freshwater fisheries: an experimental study of brook trout","year":2016,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amec Foster Wheeler (Canada); Parks Canada; Government of Newfoundland and Labrador; Memorial University of Newfoundland","funders":"","keywords":"Salvelinus; Trout; Fisheries management; Population; Fishing; Abundance (ecology); Fishery; Ecology; Population model; Geography; Environmental resource management; Environmental science; Biology; Fish <Actinopterygii>; Demography","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":[0.0001308718,0.0001102386,0.0001651815,0.00002483896,0.0002214072,0.000003987213,0.0002486458,0.0000510615,0.001825084],"category_scores_gemma":[0.00001796115,0.00007721502,0.00004190324,0.00004388457,0.0002218831,0.0001434986,0.000209954,0.00004005029,0.00007169014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002227641,"about_ca_system_score_gemma":0.00000493892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003056946,"about_ca_topic_score_gemma":0.001566653,"domain_scores_codex":[0.9990485,0.00003275422,0.0002331133,0.0003741016,0.0001065391,0.0002050147],"domain_scores_gemma":[0.9995001,0.0001074442,0.00007485854,0.0002364324,0.00001078774,0.00007040163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001105764,0.05411493,0.2239111,0.0001120491,0.000650183,0.000007123109,0.01986347,0.05822355,0.02488561,0.01841402,0.5937605,0.004951661],"study_design_scores_gemma":[0.01763539,0.01749168,0.4008858,0.00005358285,0.0007601348,0.000007852022,0.04917868,0.1185879,0.0005622664,0.08251213,0.3086881,0.003636537],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9022505,0.00002775866,0.09035267,0.001594957,0.0000612797,0.001907308,0.00001155248,0.00009322099,0.00370077],"genre_scores_gemma":[0.9923469,0.000004327379,0.00172123,0.0006415672,0.00003436107,0.003507569,0.000005781107,0.00000916179,0.001729036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2850724,"threshold_uncertainty_score":0.9990874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04428521444170135,"score_gpt":0.2503484138680125,"score_spread":0.2060631994263112,"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."}}