{"id":"W4206177129","doi":"10.1002/047147326x.ch5","title":"Model Selection and Validation","year":2003,"lang":"en","type":"other","venue":"Wiley series in probability and statistics","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Model selection; Weibull distribution; Goodness of fit; Selection (genetic algorithm); Computer science; Set (abstract data type); Model validation; Data mining; Focus (optics); Data set; Machine learning; Artificial intelligence; Statistics; Mathematics","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":[0.06280874,0.003398912,0.004119664,0.005059329,0.001905752,0.004071044,0.003733854,0.002005114,0.01823316],"category_scores_gemma":[0.2056839,0.0009778677,0.004541296,0.003749034,0.00153966,0.002657942,0.003578848,0.005406982,0.006324836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002329723,"about_ca_system_score_gemma":0.008480298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005708835,"about_ca_topic_score_gemma":0.003919127,"domain_scores_codex":[0.9541752,0.03452551,0.002220205,0.003098116,0.005235813,0.0007451003],"domain_scores_gemma":[0.9103503,0.06621668,0.002814606,0.008536605,0.01143522,0.0006465697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007911886,0.0004415603,0.01618298,0.002744207,0.002323624,0.0006792323,0.00107498,0.3236379,0.001847576,0.1323922,0.06296599,0.4549186],"study_design_scores_gemma":[0.0004153566,0.0006638183,0.00428605,0.002054517,0.0009417807,0.0004162877,0.0006919805,0.689776,0.00525857,0.1877061,0.1075402,0.0002492921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009065294,0.001753882,0.9725953,0.001543153,0.0006756384,0.002651518,0.003057801,0.001811874,0.006845679],"genre_scores_gemma":[0.1698726,0.002703414,0.7942815,0.001484841,0.0004494418,0.009725114,0.01219546,0.001581234,0.007706409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06280874,"threshold_uncertainty_score":0.3321683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08871937579510207,"score_gpt":0.3700308270345239,"score_spread":0.2813114512394218,"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."}}