{"id":"W3207497253","doi":"10.1093/gbe/evab234","title":"Genic Selection Within Prokaryotic Pangenomes","year":2021,"lang":"en","type":"review","venue":"Genome Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Servier","keywords":"Biology; Selection (genetic algorithm); Evolutionary biology; Mobile genetic elements; Niche; Gene; Stabilizing selection; Positive selection; Natural selection; Balancing selection; Negative selection; Genetics; Genetic variation; Ecology; Genome; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000718371,0.0009667156,0.001326889,0.002309052,0.0002751091,0.001251619,0.001079273,0.001483299,0.002523181],"category_scores_gemma":[0.001070531,0.000351786,0.0004335383,0.002149791,0.000851906,0.002212018,0.0009796745,0.001874943,0.001867286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000853151,"about_ca_system_score_gemma":0.001209813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009898461,"about_ca_topic_score_gemma":0.001225019,"domain_scores_codex":[0.99979,0.00003725979,0.00002787214,0.00005144823,0.00006764723,0.00002570583],"domain_scores_gemma":[0.9995062,0.0002547904,0.00007304415,0.00001858539,0.0000989019,0.00004847776],"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":[0.00006652645,0.00003044014,0.0002246454,0.02032434,0.00007518388,0.0002676167,0.0000891653,0.0006581055,0.002223454,0.01029301,0.02559278,0.9401547],"study_design_scores_gemma":[0.000006805295,0.00005043561,0.000730646,0.003338439,0.00006210167,0.001263893,0.00004766989,0.00007581679,0.0005509278,0.003163353,0.9906895,0.00002032924],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007303212,0.9987289,0.0001517744,0.0002452454,0.0001586213,0.000002070158,0.0000113677,0.000007141769,0.0006218698],"genre_scores_gemma":[0.0005979997,0.9984857,0.0001572983,0.0001964228,0.0001557006,0.00000410772,0.00002660013,0.000002171295,0.0003739228],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002523181,"threshold_uncertainty_score":0.008440912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208460120241361,"score_gpt":0.2843031095969809,"score_spread":0.2622185083945673,"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."}}