{"id":"W2045434610","doi":"10.1007/s10687-006-0028-5","title":"Extremal indices, geometric ergodicity of Markov chains, and MCMC","year":2006,"lang":"en","type":"article","venue":"Extremes","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Ergodicity; Mathematics; Markov chain; Markov chain Monte Carlo; Simple (philosophy); Stability (learning theory); Applied mathematics; Statistical physics; Pure mathematics; Statistics; Monte Carlo method; Computer science; 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":[0.009616829,0.001259718,0.002603116,0.005464852,0.001883044,0.003898408,0.002843586,0.002663002,0.0048992],"category_scores_gemma":[0.04974556,0.001217235,0.001427939,0.003151048,0.007808618,0.00623741,0.003826314,0.005486682,0.0005087613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003019845,"about_ca_system_score_gemma":0.001493358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00272992,"about_ca_topic_score_gemma":0.002729374,"domain_scores_codex":[0.9968212,0.00193652,0.000105937,0.0004496799,0.000438142,0.0002486264],"domain_scores_gemma":[0.9665421,0.02643597,0.002598945,0.00176973,0.001344644,0.001308735],"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":[0.00002610587,0.00001801758,0.0009337206,0.00004380103,0.00003521748,0.00003583128,0.00007373518,0.04261834,0.0001388633,0.9506582,0.0009599136,0.004458239],"study_design_scores_gemma":[0.000006446404,0.000006003949,0.0002564682,0.00002800954,0.000008155968,0.00002382095,0.0000177686,0.1500509,0.00007753754,0.8490348,0.0004718137,0.00001839089],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06064067,0.00385436,0.9221727,0.001736375,0.0001679722,0.00004402433,0.0002294034,0.0002746493,0.01087989],"genre_scores_gemma":[0.8465004,0.004446907,0.1387162,0.0005097048,0.0009104763,0.0002838958,0.0005894111,0.0005108464,0.007532147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009616829,"threshold_uncertainty_score":0.05085933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03880715028102013,"score_gpt":0.3000465905003925,"score_spread":0.2612394402193724,"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."}}