{"id":"W4386144974","doi":"10.1007/978-3-030-19071-2_104-1","title":"How Markov’s Little Idea Transformed Statistics","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Markov chain Monte Carlo; Markov chain; Variable-order Markov model; Computer science; Markov model; Bayesian probability; Markov chain mixing time; Mathematics; Statistical physics; Statistics; Artificial intelligence; Physics","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":[0.00150554,0.0007446213,0.0007118895,0.001614176,0.001299053,0.003807031,0.0007989678,0.001767369,0.01286455],"category_scores_gemma":[0.006984121,0.0006270703,0.0006209133,0.001326924,0.006246108,0.006448927,0.001332698,0.005067462,0.004769124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003473987,"about_ca_system_score_gemma":0.001765046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003028814,"about_ca_topic_score_gemma":0.002907043,"domain_scores_codex":[0.9989614,0.0004696041,0.00003900842,0.0001479919,0.0003306968,0.00005113994],"domain_scores_gemma":[0.9977511,0.001645531,0.00006085428,0.0002336083,0.0002527708,0.00005615609],"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":[0.000002287378,0.000002645605,0.00001326279,0.00001399928,0.000002364515,0.0000078991,0.00006193854,0.0003747182,0.00004577475,0.9897206,0.004944937,0.004809585],"study_design_scores_gemma":[0.000001668908,0.000002477847,0.00001629253,0.00001422598,0.000001846111,0.00002390945,0.00001429727,0.001122672,0.00008408177,0.969538,0.02917422,0.000006234483],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.005015028,0.01042148,0.4257084,0.01780437,0.005228483,0.00005078704,0.0004979924,0.0005118461,0.5347617],"genre_scores_gemma":[0.2905726,0.01290766,0.1230531,0.009620343,0.005941545,0.0002901919,0.0004088534,0.001625883,0.5555798],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01286455,"threshold_uncertainty_score":0.04303622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.150870108139301,"score_gpt":0.3592722762189131,"score_spread":0.2084021680796121,"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."}}