{"id":"W4403792970","doi":"10.24963/kr.2024/71","title":"Model Counting in the Wild","year":2024,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","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; National Supercomputing Centre Singapore; University of Toronto; National Research Foundation Singapore; National Research Foundation","keywords":"Computer science","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":[0.01864338,0.001863927,0.002350332,0.002543058,0.001622246,0.006817165,0.004800119,0.002075132,0.006197673],"category_scores_gemma":[0.1298145,0.001221274,0.001942775,0.003299278,0.00274696,0.0162978,0.005189203,0.00517791,0.001392121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002854756,"about_ca_system_score_gemma":0.005061544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004926123,"about_ca_topic_score_gemma":0.007636935,"domain_scores_codex":[0.9759145,0.01117184,0.001394001,0.004387847,0.006121023,0.00101079],"domain_scores_gemma":[0.9002258,0.06279166,0.004393491,0.02545455,0.005590385,0.001544127],"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":[0.0007297153,0.0003878892,0.02207274,0.0009298543,0.0005426767,0.0005404363,0.0006939035,0.3854265,0.004498139,0.3009264,0.0340863,0.2491655],"study_design_scores_gemma":[0.00004639712,0.0000735762,0.0006995581,0.00009446254,0.00005901643,0.0002328496,0.0001297378,0.7311261,0.002808946,0.2557566,0.008930171,0.00004256201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07004213,0.002299823,0.9039073,0.004876469,0.0003583624,0.0002365324,0.002132516,0.008115645,0.00803121],"genre_scores_gemma":[0.5228697,0.001114793,0.4654601,0.001548284,0.000220658,0.0003804943,0.003941136,0.002133851,0.002331041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01864338,"threshold_uncertainty_score":0.09859681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04873621218821237,"score_gpt":0.2835419759425098,"score_spread":0.2348057637542975,"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."}}