{"id":"W4242273094","doi":"10.1007/978-3-030-04756-6","title":"Population Genomics: Microorganisms","year":2019,"lang":"en","type":"book","venue":"Population genomics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Genomics; Population genomics; Audience measurement; Population; Biology; Metagenomics; Range (aeronautics); Computational biology; Genetics; Genome; Engineering; Medicine; Business; Gene; Environmental health","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":[0.0004014261,0.0004814833,0.0004938389,0.0002226369,0.0001478991,0.0001209553,0.0005499852,0.001165132,0.0001143248],"category_scores_gemma":[0.000110968,0.0005087418,0.0002759728,0.00006352204,0.00009193968,0.000008203214,0.0003896542,0.0003727604,0.0007281697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005007025,"about_ca_system_score_gemma":0.0005106881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008085644,"about_ca_topic_score_gemma":0.000116543,"domain_scores_codex":[0.9973994,0.00005502792,0.000878394,0.0006551779,0.000467591,0.0005444287],"domain_scores_gemma":[0.9981593,0.00002241536,0.0004868003,0.0008944718,0.0001951745,0.0002417868],"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":[0.001031231,0.000504968,0.03179497,0.003344859,0.001901746,0.00002184811,0.001173104,0.003256315,0.3304641,0.003889616,0.4138638,0.2087535],"study_design_scores_gemma":[0.0008998453,0.0003580992,0.0123099,0.00006503154,0.0001085908,0.00002337547,0.00003887896,0.0008607116,0.004475683,0.003086201,0.9766473,0.001126413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7073916,0.007047623,0.009393988,0.0009369361,0.009687824,0.007562494,0.002902734,0.0002941956,0.2547826],"genre_scores_gemma":[0.1031076,0.002983007,0.006968117,0.001022717,0.003893013,0.00002678442,0.05293364,0.0003344556,0.8287307],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.604284,"threshold_uncertainty_score":0.9997364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01454654390761697,"score_gpt":0.2576759009133718,"score_spread":0.2431293570057548,"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."}}