{"id":"W2099876591","doi":"10.1111/cobi.12076","title":"A Protocol for Better Design, Application, and Communication of Population Viability Analyses","year":2013,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Fisheries and Oceans Canada","funders":"","keywords":"Comparability; Protocol (science); Workflow; Computer science; Population; Management science; Operations research; Risk analysis (engineering); Environmental resource management; Engineering; Environmental science; Business; Medicine; Mathematics","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":[0.0001781552,0.00005032522,0.00008221858,0.00001443046,0.00006679468,0.000008005384,0.00007155623,0.00005499995,0.003216478],"category_scores_gemma":[0.00008933647,0.00004259058,0.00001713036,0.00009288425,0.0001539824,0.00009835128,0.00004016537,0.00001955096,0.00003410399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005559481,"about_ca_system_score_gemma":0.000002488472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001163515,"about_ca_topic_score_gemma":0.0001365233,"domain_scores_codex":[0.9994979,0.0000812947,0.0001940094,0.0001258801,0.00003263805,0.00006830534],"domain_scores_gemma":[0.9994895,0.0001288167,0.0001367825,0.0001758372,0.00004859533,0.00002039752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000282298,0.00006342457,0.9012553,0.00002563473,0.000005975719,2.409781e-9,0.0000583527,0.00000889465,0.0824808,0.002335687,0.006888055,0.006849648],"study_design_scores_gemma":[0.0003417267,0.00004856651,0.9712218,0.000002333922,0.00000469824,2.815459e-7,0.00005142635,0.002723614,0.002962985,0.01002986,0.0125542,0.00005847976],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7811936,0.000006079984,0.09834751,0.006859825,0.00001409149,0.1127616,0.00003581498,0.00005327011,0.0007282533],"genre_scores_gemma":[0.8032392,0.000001581487,0.005647925,0.0008264466,0.000005680175,0.1899254,0.0003176105,0.000004213094,0.00003187064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09269959,"threshold_uncertainty_score":0.9976947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1451034403512885,"score_gpt":0.3833293158134938,"score_spread":0.2382258754622054,"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."}}