{"id":"W4403673597","doi":"10.1090/cln/033/02","title":"Markov chains (I)","year":2024,"lang":"en","type":"book-chapter","venue":"Courant lecture notes in mathematics","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Markov chain; Computer science; Machine learning","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":[0.001560759,0.001110012,0.001670079,0.0006029166,0.0000838542,0.0001325088,0.0006394835,0.001287153,0.000538131],"category_scores_gemma":[0.001377641,0.0009107396,0.0006949049,0.0001429513,0.000178278,0.00004808368,0.0002933349,0.001892886,0.00001574053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003212602,"about_ca_system_score_gemma":0.0001567386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003645233,"about_ca_topic_score_gemma":0.0001995806,"domain_scores_codex":[0.9963569,0.00005054926,0.001299003,0.0008259115,0.0008112844,0.0006563689],"domain_scores_gemma":[0.9944571,0.003342252,0.000478489,0.001381607,0.0001668146,0.0001737939],"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":[0.00002521172,0.0001188557,0.000001728598,0.008837047,0.0003320612,0.0005420261,0.002802555,0.0000333457,0.000116978,0.9708372,0.003621768,0.01273127],"study_design_scores_gemma":[0.000312784,0.0000625317,1.224894e-7,0.003637932,0.0003936336,0.0001499212,0.00002752237,0.005491972,0.0001241548,0.9288576,0.05997231,0.0009694739],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005908499,0.006575286,0.1770772,0.0007721088,0.001416368,0.001317274,0.0001744901,0.0004305115,0.8121777],"genre_scores_gemma":[0.002315518,0.002006756,0.3167252,0.0003602049,0.001477398,0.0001031922,0.00006986934,0.0009779535,0.6759639],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1396479,"threshold_uncertainty_score":0.9993343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05304127864922607,"score_gpt":0.3237377894647118,"score_spread":0.2706965108154857,"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."}}