{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005365306,0.0001341025,0.0001241931,0.00003119859,0.00008195323,0.00002997187,0.0001010169,0.0002459391,0.00000733588],"category_scores_gemma":[0.00002226623,0.0001475428,0.00004683762,0.00003067912,0.00002010974,0.000001536647,0.0001077341,0.00005051923,0.00000842387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008312238,"about_ca_system_score_gemma":0.00001365986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005384141,"about_ca_topic_score_gemma":0.00005827165,"domain_scores_codex":[0.9993873,0.00001976916,0.0001345609,0.0002891998,0.00007332255,0.00009586933],"domain_scores_gemma":[0.9996197,0.000004928532,0.0001049281,0.0001851465,0.00002973385,0.00005555336],"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":[0.00004915502,0.000004644856,0.0003156849,0.0001515592,0.00006380428,7.779165e-7,0.000007532538,0.00001655342,0.00008990833,0.00008187962,0.9985285,0.0006899512],"study_design_scores_gemma":[0.0002909507,0.00006545593,0.007459257,0.000008414385,0.0001134745,0.000002630715,0.00001284706,0.00002383569,0.00004691694,0.0002075814,0.9916106,0.0001580187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004503184,0.00008798111,0.0004875304,0.0005300524,0.0002440112,0.0004548091,0.9936639,0.000006498517,0.00002205337],"genre_scores_gemma":[0.001074985,0.0005189533,0.001855764,0.001753444,0.0002223235,0.00001553938,0.9943933,0.000009561619,0.000156162],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007143572,"threshold_uncertainty_score":0.601662,"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."}}