{"id":"W2970048450","doi":"10.1038/s41592-019-0532-6","title":"Markov models — hidden Markov models","year":2019,"lang":"en","type":"article","venue":"Nature Methods","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Hidden Markov model; Markov chain; Computer science; Markov model; Computational biology; Artificial intelligence; Machine learning; Biology","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":[0.002024119,0.0003153245,0.0004080452,0.0001767785,0.00009919928,0.0002390558,0.001861503,0.0006546241,0.00006447479],"category_scores_gemma":[0.00006949115,0.0002735981,0.0001749669,0.000592774,0.0000359286,0.001122442,0.0005024159,0.001322404,0.00008844298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006503607,"about_ca_system_score_gemma":0.0001490755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000219719,"about_ca_topic_score_gemma":0.000001554906,"domain_scores_codex":[0.9971292,0.0005861197,0.0003375175,0.0008816381,0.0005079452,0.0005575833],"domain_scores_gemma":[0.9976422,0.0003647933,0.0001206184,0.001453207,0.0002168524,0.0002023146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001906653,0.00004551945,0.00002366912,0.00003638593,0.00003562353,0.000009451344,0.000383835,0.003483077,0.001817968,0.3769386,0.002699535,0.6145073],"study_design_scores_gemma":[0.0001846404,0.00003568209,0.00003286994,0.00002984412,0.00000801821,0.00001675727,0.000008327358,0.6949157,0.001153228,0.3021882,0.001150302,0.0002764143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001269171,0.001911739,0.9322776,0.0009688396,0.001402522,0.0002226196,0.000004228338,0.0003518234,0.06159143],"genre_scores_gemma":[0.2278678,0.00005335819,0.7674671,0.001516883,0.0001018505,0.00001417711,0.000003166679,0.00002372776,0.002951883],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6914327,"threshold_uncertainty_score":0.9999716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932966308427788,"score_gpt":0.3414510419929232,"score_spread":0.3121213789086453,"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."}}