{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005431336,0.0002013937,0.0003203809,0.0003960712,0.0001786765,0.0004231147,0.001426611,0.0001486715,0.00004242042],"category_scores_gemma":[0.0003526055,0.0001980547,0.000090338,0.000115468,0.00009425032,0.00008279833,0.0001131988,0.001063166,0.00001399601],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021594,"about_ca_system_score_gemma":0.00794251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001707452,"about_ca_topic_score_gemma":0.003716494,"domain_scores_codex":[0.9985582,0.00007068257,0.0004660672,0.0002281996,0.0003185509,0.0003583072],"domain_scores_gemma":[0.9975019,0.00008204431,0.0006178904,0.0004398526,0.0006106486,0.000747685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007677669,0.00003707734,0.001672453,0.0003537482,0.000165277,0.002191455,0.003105781,0.6888334,0.000008913041,0.04079603,0.1072868,0.1555414],"study_design_scores_gemma":[0.0001632874,0.00006595765,0.0004105442,0.000221776,0.00002291156,0.00004577598,0.000004628988,0.9678224,0.0000135024,0.02674402,0.004270802,0.0002144176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006578073,0.0001906194,0.9957047,0.0006816822,0.001767228,0.00005486235,0.000191455,0.00001477256,0.0007368601],"genre_scores_gemma":[0.1558333,0.000008643178,0.8429654,0.0004205326,0.0004927718,8.606188e-7,0.00001157833,0.00002220587,0.0002447242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.278989,"threshold_uncertainty_score":0.9976816,"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."}}