{"id":"W4400586448","doi":"10.1007/978-3-031-59762-6_15","title":"Simple Stratified Sampling for Simulating Multi-dimensional Markov Chains","year":2024,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Simple (philosophy); Markov chain; Stratified sampling; Simple random sample; Sampling (signal processing); Markov chain Monte Carlo; Computer science; Statistical physics; Mathematics; Statistics; Artificial intelligence; Physics; Bayesian probability; Sociology; Computer vision","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":[0.001448545,0.001026014,0.00139626,0.0005427678,0.0002121276,0.0004127197,0.0004508902,0.0006947425,0.0005620874],"category_scores_gemma":[0.002786318,0.0009568988,0.0003125928,0.0001162005,0.0001571303,0.0001861183,0.00023974,0.001097251,0.0001354735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003765759,"about_ca_system_score_gemma":0.0001457329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003316626,"about_ca_topic_score_gemma":0.00004808412,"domain_scores_codex":[0.994937,0.000007213259,0.002423348,0.0009527334,0.0009601819,0.0007195258],"domain_scores_gemma":[0.9952955,0.00221114,0.001072965,0.0004060279,0.0008070816,0.0002072402],"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":[0.00001967716,0.000206645,0.000001894728,0.01041244,0.0001367798,0.000008603226,0.001621486,0.00001497597,0.0001738175,0.9839106,0.002425142,0.001068007],"study_design_scores_gemma":[0.0004710922,0.00007251465,0.000001198399,0.002023012,0.000224915,0.000008903963,0.0002202014,0.260676,0.0001190057,0.7311966,0.00427017,0.0007163502],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006724408,0.0001751921,0.7944463,0.0001522765,0.0005635374,0.005252625,0.001551056,0.0007035456,0.196483],"genre_scores_gemma":[0.0005138863,0.00002412746,0.8086438,0.00005729724,0.0002798837,0.0002321889,0.0001868123,0.0003892927,0.1896728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.260661,"threshold_uncertainty_score":0.9992881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09711208453814947,"score_gpt":0.3555192844838213,"score_spread":0.2584071999456718,"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."}}