{"id":"W2890872080","doi":"10.1007/13836_2018_45","title":"Advances in Using Non-invasive, Archival, and Environmental Samples for Population Genomic Studies","year":2018,"lang":"en","type":"book-chapter","venue":"Population genomics","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Metagenomics; Biology; Genotyping; DNA sequencing; Evolutionary biology; Molecular ecology; Population; Computational biology; Ecology; Genetics; DNA; Genotype; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001521251,0.0004187081,0.0004671072,0.0001241579,0.000363333,0.00002372617,0.0001659065,0.0001521291,0.0001496091],"category_scores_gemma":[0.00002117931,0.0004722244,0.0001026181,0.00001998677,0.0004534258,0.0002914593,0.0005630991,0.0001277512,0.00007779667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508597,"about_ca_system_score_gemma":0.00000309574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000178585,"about_ca_topic_score_gemma":0.0005472067,"domain_scores_codex":[0.9982651,0.00001799512,0.0004772178,0.0007103684,0.0002306088,0.0002986866],"domain_scores_gemma":[0.9991792,0.0001182926,0.0003825709,0.0002472126,0.000002898297,0.000069822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009053228,0.00004534385,0.9799281,0.0001476467,0.00009310679,0.000003417786,0.001434495,0.006261773,0.00309578,0.0002064171,0.0001983124,0.008495041],"study_design_scores_gemma":[0.0007570053,0.0001610712,0.9576322,0.000143018,0.0001984567,0.000009296299,0.0004911048,0.001305901,0.0001212809,0.02290665,0.01525822,0.001015735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937994,0.001926186,0.0001693206,0.00001773814,0.000254156,0.001140909,0.0005026934,0.00001865395,0.002170904],"genre_scores_gemma":[0.8969252,0.03475893,0.05521156,0.0002124649,0.000449027,0.000052095,0.002024362,0.0001890089,0.01017733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09687421,"threshold_uncertainty_score":0.999773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04227262930711022,"score_gpt":0.2581471007299935,"score_spread":0.2158744714228833,"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."}}