{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006268191,0.002109129,0.002557834,0.002919644,0.001047117,0.005535861,0.004067649,0.004622457,0.01088301],"category_scores_gemma":[0.04894514,0.001783916,0.00176875,0.004358619,0.003281303,0.008326379,0.003076112,0.006404358,0.004380325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002004571,"about_ca_system_score_gemma":0.002770403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003786272,"about_ca_topic_score_gemma":0.002891612,"domain_scores_codex":[0.9932781,0.004514503,0.0002258812,0.0009304081,0.0008917239,0.0001593758],"domain_scores_gemma":[0.973726,0.02146156,0.001453519,0.001760015,0.001130182,0.0004687114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007299038,0.00007019711,0.0008464438,0.0005861897,0.0001577019,0.0001087946,0.0001301626,0.06994465,0.0005403692,0.85028,0.01270489,0.06455763],"study_design_scores_gemma":[0.00001868999,0.000006418476,0.0001366871,0.00007257577,0.00002927408,0.00005137168,0.00001513233,0.1451088,0.0001430181,0.8466821,0.007711819,0.00002401972],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009187982,0.004618283,0.9884855,0.001321457,0.0003508226,0.00004421167,0.0004282573,0.0003718488,0.003460985],"genre_scores_gemma":[0.1876715,0.0198148,0.7665131,0.002693399,0.004040449,0.001079908,0.002526764,0.001042155,0.01461787],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01088301,"threshold_uncertainty_score":0.03640729,"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."}}