{"id":"W2128306307","doi":"10.5555/1161734.1161967","title":"Decision tree module within decision support simulation system","year":2004,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Decision tree; Computer science; Decision support system; Incremental decision tree; Probabilistic logic; Shortest path problem; Tree (set theory); Influence diagram; Decision analysis; Data mining; Decision tree learning; Machine learning; Artificial intelligence; Theoretical computer science; Mathematics; Statistics; Graph","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001429721,0.0005516412,0.0005218479,0.0008639005,0.0003772729,0.001433179,0.0012067,0.0008067625,0.01553562],"category_scores_gemma":[0.003647016,0.0003751644,0.0006539816,0.0007218056,0.0003089416,0.001564859,0.0008657022,0.001024604,0.005399236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004856361,"about_ca_system_score_gemma":0.001088608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001494664,"about_ca_topic_score_gemma":0.0007732692,"domain_scores_codex":[0.9990102,0.0003658083,0.0001123329,0.0001863608,0.0002583304,0.00006694192],"domain_scores_gemma":[0.9986176,0.0007136705,0.00008251258,0.0001975233,0.0002986654,0.00008997098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008336612,0.0004659924,0.004889784,0.0006893505,0.0002427561,0.0005465266,0.0007457741,0.3331161,0.01478999,0.1558077,0.05328797,0.4345843],"study_design_scores_gemma":[0.0001268334,0.0001244543,0.0005058583,0.00007593516,0.00006420407,0.0001769478,0.00003876521,0.8236329,0.01434117,0.04644426,0.1144189,0.00004974876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006182897,0.000105885,0.9617413,0.000207065,0.00007452448,0.0003409501,0.0009867967,0.0205872,0.009773449],"genre_scores_gemma":[0.2178552,0.0004127819,0.7615859,0.0004532536,0.0001094108,0.001327183,0.003939166,0.002126304,0.01219076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01553562,"threshold_uncertainty_score":0.05197185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04269106624299621,"score_gpt":0.3030428193550132,"score_spread":0.260351753112017,"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."}}