{"id":"W2315710929","doi":"10.1139/f2011-175","title":"Low-cost estimates of mortality rate from single tag recoveries: addressing short-term trap-happy and trap-shy bias","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trap (plumbing); Statistics; Estimator; Stock assessment; Econometrics; Maximum likelihood; Mortality rate; Stock (firearms); Biology; Mathematics; Environmental science; Fishery; Demography; Geography; 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":[0.009004761,0.0005030197,0.0006197022,0.001029409,0.0002097973,0.0007128884,0.001226383,0.0006952083,0.0006733355],"category_scores_gemma":[0.0406923,0.0003476241,0.0004327858,0.0006766146,0.0003668963,0.001135272,0.001129917,0.000597525,0.0002580871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000609643,"about_ca_system_score_gemma":0.0004483617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002243594,"about_ca_topic_score_gemma":0.004217408,"domain_scores_codex":[0.9974614,0.001416761,0.0001294954,0.0003369559,0.000565974,0.00008937467],"domain_scores_gemma":[0.9789726,0.01346285,0.003491004,0.002252298,0.00165768,0.0001635823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007638424,0.0002283523,0.3317005,0.0005197931,0.0008562088,0.0002465033,0.0005572052,0.2352253,0.0215251,0.01378497,0.001168424,0.3934237],"study_design_scores_gemma":[0.00005450927,0.0003919544,0.1749767,0.00009304833,0.0002173437,0.0004805887,0.0001482601,0.7924371,0.01613252,0.01339318,0.001516513,0.0001581514],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3100121,0.0006663892,0.6875221,0.0001535715,0.00002418477,0.00006812472,0.0003792974,0.0003127628,0.0008614412],"genre_scores_gemma":[0.7590959,0.0002977999,0.2382906,0.0000820013,0.00004698043,0.00009709242,0.0007568845,0.00008802424,0.001244674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009004761,"threshold_uncertainty_score":0.04762226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07755706347458845,"score_gpt":0.2625281589272505,"score_spread":0.184971095452662,"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."}}