{"id":"W2160639001","doi":"10.1214/ecp.v12-1336","title":"On Variance Conditions for Markov Chain CLTs","year":2007,"lang":"en","type":"article","venue":"Electronic Communications in Probability","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics; Markov chain; Variance (accounting); Limit (mathematics); Chain (unit); Applied mathematics; Econometrics; Statistics; Mathematical analysis; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.007205604,0.0001725113,0.0002720759,0.0001267721,0.0002660348,0.00001848475,0.000834872,0.0001286065,0.00002512793],"category_scores_gemma":[0.003297673,0.0001764967,0.0001276187,0.0004011761,0.0001829251,0.00006759358,0.0001619776,0.0005291136,3.115207e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007379062,"about_ca_system_score_gemma":0.0002002592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002525746,"about_ca_topic_score_gemma":0.003817907,"domain_scores_codex":[0.9979278,0.000428443,0.0005782151,0.0003357515,0.0001413919,0.0005883746],"domain_scores_gemma":[0.9910162,0.005906191,0.0001562359,0.002705899,0.000149449,0.00006604371],"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":[0.00008566533,0.000663875,0.0001955802,0.00005253642,0.00001836676,2.208159e-7,0.0002597657,0.000006276006,0.0001976369,0.9876906,0.0007021505,0.01012737],"study_design_scores_gemma":[0.0007764936,0.0001722911,0.0005983278,0.00004843747,0.00001816366,0.000003341345,0.00007332058,0.001899939,0.0003355492,0.979284,0.01658639,0.0002036807],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3690447,0.001259098,0.5182913,0.01002025,0.0003700434,0.008390993,0.0001486039,0.0005088648,0.09196614],"genre_scores_gemma":[0.858215,0.00007079901,0.140077,0.0001970351,0.000029201,0.0006828893,0.00004382402,0.00002591294,0.00065836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4891703,"threshold_uncertainty_score":0.7197328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07906550605768099,"score_gpt":0.4114142508277198,"score_spread":0.3323487447700388,"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."}}