{"id":"W3095888007","doi":"10.1007/13836_2020_83","title":"Wildlife Population Genomics: Applications and Approaches","year":2020,"lang":"en","type":"book-chapter","venue":"Population genomics","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Wildlife; Genomics; Population genomics; Metagenomics; Population; Biology; Wildlife conservation; Biodiversity; Data science; Environmental resource management; Geography; Ecology; Computer science; Genome; Genetics","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":[0.001017822,0.000594297,0.0004771918,0.001381286,0.0004747753,0.002783927,0.001018334,0.001147593,0.01925976],"category_scores_gemma":[0.001031819,0.0003798992,0.0003297193,0.002113175,0.001381096,0.00224025,0.001163617,0.001497186,0.00537759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009682817,"about_ca_system_score_gemma":0.0008419642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001710258,"about_ca_topic_score_gemma":0.00454392,"domain_scores_codex":[0.9997178,0.00007500911,0.000009055028,0.00005031102,0.0001308407,0.00001697815],"domain_scores_gemma":[0.9996792,0.000203569,0.00001155332,0.00002819057,0.00005046732,0.0000270975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008964974,0.00004001944,0.0004760231,0.0005064578,0.00001625021,0.00007124692,0.0003800018,0.00122254,0.001439931,0.2738921,0.1517596,0.5701869],"study_design_scores_gemma":[0.00000245593,0.00001147998,0.0007373168,0.0002627692,0.000007445307,0.0002560604,0.0001725728,0.0008187465,0.0004722278,0.1071038,0.8901437,0.00001150563],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.003288422,0.1699987,0.19901,0.01364342,0.004826167,0.0001438222,0.0008451737,0.001076599,0.6071678],"genre_scores_gemma":[0.0258311,0.1805626,0.1904094,0.01015395,0.003446158,0.0004179972,0.001403986,0.000792356,0.5869825],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01925976,"threshold_uncertainty_score":0.0644303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03897377935991525,"score_gpt":0.1982253391225223,"score_spread":0.159251559762607,"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."}}