{"id":"W2093614514","doi":"10.1239/jap/1421763335","title":"The Containment Condition and Adapfail Algorithms","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Probability","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Containment (computer programming); Mathematics; Markov chain Monte Carlo; Markov chain; Convergence (economics); Ergodic theory; Algorithm; Focus (optics); Mathematical optimization; Monte Carlo method; Computer science; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009628472,0.0008862781,0.001588687,0.001169222,0.001104686,0.002301301,0.00302282,0.002769791,0.008708584],"category_scores_gemma":[0.07340489,0.0006678079,0.0008351544,0.001060422,0.003712327,0.005556748,0.004913811,0.004437412,0.002171613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290862,"about_ca_system_score_gemma":0.001841094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001116819,"about_ca_topic_score_gemma":0.0006823312,"domain_scores_codex":[0.991419,0.004254064,0.0004195568,0.001080752,0.002345178,0.0004814937],"domain_scores_gemma":[0.9368843,0.04603238,0.00286243,0.008543902,0.004573958,0.001103115],"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":[0.0004516398,0.0001359254,0.003085169,0.0002467787,0.00007655426,0.0002045508,0.0002922544,0.1478814,0.002538337,0.7174537,0.00869707,0.1189365],"study_design_scores_gemma":[0.00005405046,0.0001709143,0.0003323908,0.00006498772,0.00001687679,0.0002218915,0.00003982953,0.7075333,0.003153732,0.2826202,0.005766358,0.00002548895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01757256,0.0005954352,0.9699365,0.000961939,0.000125571,0.0001041853,0.0001095483,0.0006274465,0.009966752],"genre_scores_gemma":[0.6346971,0.0009512995,0.3497655,0.00159644,0.0005403627,0.0007838168,0.000638278,0.0008001026,0.01022702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009628472,"threshold_uncertainty_score":0.05092084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03507870658301528,"score_gpt":0.3129043659661507,"score_spread":0.2778256593831355,"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."}}