{"id":"W2950806088","doi":"10.1101/011502","title":"Full-genome evolutionary histories of selfing, splitting and selection in <i>Caenorhabditis</i>","year":2014,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Selfing; Caenorhabditis; Selection (genetic algorithm); Caenorhabditis elegans; Biology; Genome; Evolutionary biology; Genetics; Computer science; Gene; Artificial intelligence; Sociology; Demography; Population","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":[0.0004961946,0.0001473552,0.0002200211,0.0008205418,0.0005203553,0.0003671766,0.0003604881,0.00033147,0.001038461],"category_scores_gemma":[0.0008754965,0.0002127881,0.0004384333,0.0006769881,0.0003206885,0.0003048163,0.0003511717,0.0004045031,0.0001504988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006352993,"about_ca_system_score_gemma":0.0002726608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007609733,"about_ca_topic_score_gemma":0.01508958,"domain_scores_codex":[0.9998826,0.00002604911,0.000006629318,0.00004867905,0.0000169672,0.00001902868],"domain_scores_gemma":[0.9995634,0.0002006798,0.00007051045,0.0000546945,0.00003801316,0.00007264595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001417453,0.0002222343,0.5272039,0.0003020159,0.001193418,0.0008166329,0.0009511929,0.05414531,0.3815299,0.003973722,0.001011744,0.02723261],"study_design_scores_gemma":[0.00003778318,0.0001957602,0.9369372,0.00002610954,0.0001953124,0.0003632712,0.0002616385,0.053085,0.005431961,0.001565464,0.00184958,0.00005083837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989722,0.00005504822,0.0004589315,0.00001112919,8.462372e-7,0.000002152579,0.0002884002,0.00001679718,0.0001944894],"genre_scores_gemma":[0.9980066,0.00004299083,0.0007841474,0.00001656095,9.729426e-7,0.000005490282,0.001053809,0.0000123486,0.00007715152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007609733,"threshold_uncertainty_score":0.01513088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00446583648725396,"score_gpt":0.1936412423646262,"score_spread":0.1891754058773722,"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."}}