{"id":"W2056220746","doi":"10.1111/faf.12027","title":"Natural mortality estimators for information‐limited fisheries","year":2013,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":195,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"","keywords":"Estimator; Stock assessment; Fishery; Statistics; Stock (firearms); Econometrics; Biology; Mathematics; Computer science; Fishing; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007950352,0.0001323818,0.0001448556,0.00002070459,0.0003560038,0.000120173,0.0001098197,0.00005905983,0.001476282],"category_scores_gemma":[0.0001397598,0.0001150059,0.00003413485,0.00008956961,0.0003776505,0.001729829,0.0001920429,0.00006752741,0.0001100224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002047579,"about_ca_system_score_gemma":0.000002874251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002481121,"about_ca_topic_score_gemma":0.001252234,"domain_scores_codex":[0.9993142,0.00001202574,0.0001792947,0.0001515664,0.00009667183,0.0002462534],"domain_scores_gemma":[0.9996817,0.00005986812,0.00006301281,0.0001266636,0.00001731146,0.0000514443],"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":[0.000007101487,0.000008718738,0.4609083,0.00002233762,0.00002228911,2.300306e-7,0.0003144272,0.000002011391,0.000002646185,0.0001028218,0.5370259,0.001583283],"study_design_scores_gemma":[0.0001974908,0.00004320532,0.7959468,0.000002193262,0.00001482784,0.000001019771,0.0003434694,0.0003559231,0.00001749132,0.001356073,0.2015922,0.0001292388],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9436115,0.000009189408,0.0002381441,0.009460126,0.0003758701,0.0006747482,0.00003290583,0.0001320639,0.04546548],"genre_scores_gemma":[0.9846583,0.00004239364,0.002021077,0.01013786,0.00003265009,0.0004252091,0.0000895095,0.000008634214,0.00258439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3354336,"threshold_uncertainty_score":0.9994365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008864456508758315,"score_gpt":0.1981163517454087,"score_spread":0.1892518952366504,"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."}}