{"id":"W4281655963","doi":"10.1145/3535508.3545563","title":"EvoVGM","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Sequence (biology); Robustness (evolution); Artificial intelligence; Hidden Markov model; Bayesian probability; Consistency (knowledge bases); Inference; Markov chain Monte Carlo; Generative model; Bayesian inference; Estimator; Algorithm; Generative grammar; Mathematics; Biology","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":[0.001291675,0.0008583292,0.0009630347,0.0007130988,0.0005007104,0.001280864,0.002906286,0.002431344,0.00794414],"category_scores_gemma":[0.004551263,0.0007390418,0.001209591,0.0007817891,0.0007491526,0.001448347,0.002040679,0.002142627,0.002658396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115264,"about_ca_system_score_gemma":0.001757583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007245131,"about_ca_topic_score_gemma":0.00892151,"domain_scores_codex":[0.9994124,0.0002018396,0.0000315389,0.0001516178,0.0001388097,0.00006370937],"domain_scores_gemma":[0.9991977,0.0004073537,0.00005004874,0.0001670804,0.0001287766,0.00004909822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008185568,0.00005484289,0.0009020821,0.0001221998,0.0001118133,0.00009485939,0.0001013714,0.8138679,0.001917035,0.05979058,0.008406986,0.1145485],"study_design_scores_gemma":[0.00000856661,0.000007745696,0.0000444953,0.000009518114,0.000005501107,0.00002407241,0.000005164822,0.9758986,0.0004673882,0.02059268,0.002930701,0.000005441416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005722289,0.0002957116,0.9871123,0.0002555529,0.00007271598,0.00006607266,0.000490045,0.003196112,0.002789269],"genre_scores_gemma":[0.254851,0.00059202,0.7278275,0.0008228832,0.0001297757,0.0004697386,0.003351811,0.002653898,0.009301312],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.00794414,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533553516869206,"score_gpt":0.2548874168265456,"score_spread":0.2395518816578535,"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."}}