{"id":"W4238320961","doi":"10.1007/978-1-4614-6170-8_100374","title":"Markov Chain Monte Carlo Algorithms","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Markov chain Monte Carlo; Computer science; Monte Carlo method; Markov chain; Algorithm; Hybrid Monte Carlo; Statistical physics; Mathematics; Machine learning; Statistics; 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":[0.001629957,0.001458683,0.001607272,0.001514649,0.0006153258,0.002358913,0.001736052,0.001699081,0.02374447],"category_scores_gemma":[0.007773424,0.0008196372,0.0008933209,0.002342899,0.001215129,0.002384895,0.001506743,0.002619299,0.01049167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183889,"about_ca_system_score_gemma":0.001870519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00288879,"about_ca_topic_score_gemma":0.002929438,"domain_scores_codex":[0.9983217,0.0007051201,0.0000574778,0.0002146254,0.0006303446,0.00007064565],"domain_scores_gemma":[0.9965873,0.002480034,0.00008411719,0.0003831908,0.0004069006,0.00005852278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002865848,0.00006881359,0.0002376045,0.0002083437,0.0000563883,0.00004166446,0.00006507899,0.1740578,0.0003095485,0.5235722,0.03427058,0.2670832],"study_design_scores_gemma":[0.00001571941,0.0000110238,0.00009991101,0.0001285083,0.00002014538,0.00007127241,0.0000155537,0.4006322,0.0006177356,0.5280298,0.07033201,0.00002604948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003906316,0.001750172,0.9668645,0.0002984623,0.0002028366,0.00003443544,0.0001165196,0.0005843775,0.02975807],"genre_scores_gemma":[0.06233397,0.009138549,0.8396789,0.0005900251,0.0007241759,0.0004770419,0.001216052,0.001195941,0.08464538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02374447,"threshold_uncertainty_score":0.07943314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054902968906671,"score_gpt":0.3777219659269885,"score_spread":0.2722316690363213,"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."}}