{"id":"W2282418172","doi":"","title":"A Comparison of Modeling Scales in Flexible Parametric Models","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Akaike information criterion; Statistics; Proportional hazards model; Survival analysis; Accelerated failure time model; Parametric statistics; Scale (ratio); Probit model; Parametric model; Weibull distribution; Econometrics; Medicine; Mathematics; Computer science; Geography; Cartography","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":[0.07602428,0.001384013,0.001313067,0.002737305,0.0008534745,0.004974118,0.00236977,0.001437257,0.004052132],"category_scores_gemma":[0.2458703,0.0005601883,0.00346423,0.003835645,0.00204381,0.004765221,0.003822691,0.003003523,0.0005916015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970366,"about_ca_system_score_gemma":0.00189563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00302309,"about_ca_topic_score_gemma":0.001669806,"domain_scores_codex":[0.9442097,0.04549731,0.001662932,0.003427899,0.004233391,0.000968691],"domain_scores_gemma":[0.6263293,0.3318311,0.0133886,0.01966548,0.006819369,0.001966148],"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":[0.003687527,0.0005444493,0.1301842,0.001598285,0.003595609,0.0008843202,0.003455844,0.3472773,0.001192392,0.2927944,0.01743976,0.1973458],"study_design_scores_gemma":[0.0004324522,0.001540105,0.04286524,0.0007456583,0.0008859815,0.0005748934,0.002246838,0.6410206,0.0009357307,0.2941596,0.01429,0.0003029517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.33417,0.006289893,0.6381583,0.003950363,0.0004850809,0.0006919081,0.003418044,0.000848147,0.01198838],"genre_scores_gemma":[0.8943298,0.001428075,0.09882396,0.0004415116,0.0002436334,0.0007700209,0.002767372,0.0003688739,0.0008268212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07602428,"threshold_uncertainty_score":0.4020596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1703339086319744,"score_gpt":0.4184569450291712,"score_spread":0.2481230363971969,"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."}}