{"id":"W3028587974","doi":"10.22541/au.158480040.06912807","title":"Population genomics for wildlife conservation and management","year":2020,"lang":"en","type":"dataset","venue":"Authorea","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Wildlife; Population genomics; Population; Adaptive management; Wildlife conservation; Genomics; Conservation biology; Wildlife management; Conservation genetics; Environmental resource management; Biodiversity; Minimum viable population; Population size; Geography; Biology; Ecology; Endangered species; Genome; Genetics; Environmental science","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":[0.003605148,0.001341853,0.001510007,0.003746565,0.0008439626,0.002924061,0.003418999,0.001824073,0.1379087],"category_scores_gemma":[0.02021073,0.0007118457,0.001309177,0.009577733,0.0003879701,0.002547131,0.003477945,0.002547392,0.06918662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593468,"about_ca_system_score_gemma":0.00324171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01787441,"about_ca_topic_score_gemma":0.02873681,"domain_scores_codex":[0.9983702,0.0005636045,0.0002120735,0.000454118,0.0002577178,0.0001423273],"domain_scores_gemma":[0.9934759,0.002927283,0.0006796377,0.001426812,0.0009163991,0.0005739986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007594447,0.00001673234,0.003314727,0.001882061,0.0001328509,0.00003612056,0.00005604009,0.0005293667,0.000091792,0.004200843,0.9759754,0.01368807],"study_design_scores_gemma":[0.0001822295,0.00001096828,0.006047753,0.0008771859,0.0000620508,0.00005694862,0.0000568369,0.0003609926,0.0001028355,0.007754464,0.9844637,0.00002408816],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001419023,0.0003532352,0.0005621835,0.0003571715,0.00004106896,0.00002025063,0.9964234,0.0004356057,0.001665222],"genre_scores_gemma":[0.001345858,0.0004615235,0.002853446,0.0003305826,0.00002741704,0.0002564758,0.9934197,0.0002597583,0.001045236],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1379087,"threshold_uncertainty_score":0.4613505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897379540844675,"score_gpt":0.252270956279692,"score_spread":0.2332971608712452,"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."}}