{"id":"W2469206972","doi":"10.1002/cjs.11457","title":"Prior‐based model checking","year":2018,"lang":"en","type":"preprint","venue":"Canadian Journal of Statistics","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Process (computing); Model checking; Dirichlet process; Algorithm; Theoretical computer science; Mathematical optimization; Artificial intelligence; Mathematics; Programming language; Bayesian probability","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.02377759,0.001984324,0.002729508,0.003924745,0.001803694,0.006267603,0.006093125,0.002592529,0.01085823],"category_scores_gemma":[0.1339281,0.001467385,0.004551728,0.002842777,0.004127908,0.007430986,0.006691587,0.005252502,0.00187495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003561703,"about_ca_system_score_gemma":0.007115356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007300023,"about_ca_topic_score_gemma":0.008400591,"domain_scores_codex":[0.9672555,0.01741652,0.001599029,0.004033982,0.008025569,0.001669342],"domain_scores_gemma":[0.8560711,0.1078067,0.00499327,0.02028447,0.009654316,0.001190198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006380239,0.0002270999,0.003770958,0.0004825123,0.0004319816,0.0003814207,0.0006552931,0.5771974,0.003037351,0.2690023,0.005402367,0.1387732],"study_design_scores_gemma":[0.00003743362,0.00003082811,0.0001384721,0.000057862,0.00003660101,0.00005159621,0.00003253149,0.8500429,0.002742066,0.1457415,0.001062067,0.0000260803],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008017562,0.000111406,0.9876813,0.0003993647,0.00004002476,0.0001094807,0.0002463768,0.001714592,0.001679926],"genre_scores_gemma":[0.4849254,0.000205977,0.5088783,0.0004461391,0.0001229369,0.0004598465,0.001288668,0.0008231862,0.002849531],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02377759,"threshold_uncertainty_score":0.1257494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954156141180301,"score_gpt":0.2616255454843285,"score_spread":0.2320839840725255,"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."}}