{"id":"W2104778490","doi":"10.4172/2155-6180.1000109","title":"A Comparison of Generalized Additive Models to Other Common Modeling Strategies for Continuous Covariates: Implications for Risk Adjustment","year":2011,"lang":"en","type":"article","venue":"Journal of Biometrics & Biostatistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ministry of Labour, Employment and Social Solidarity; Université Laval; Hôpital de l'Enfant-Jésus","funders":"Canadian Institutes of Health Research; Canadian Health Services Research Foundation","keywords":"Covariate; Computer science; Generalized additive model; Econometrics; Machine learning; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.1118767,0.002460863,0.002824445,0.002658779,0.0009213963,0.0028151,0.003854525,0.001404121,0.001556358],"category_scores_gemma":[0.2516603,0.0009713327,0.005273789,0.004120936,0.001361016,0.002709077,0.002794297,0.003347893,0.0003032873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002684351,"about_ca_system_score_gemma":0.004587906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03919001,"about_ca_topic_score_gemma":0.04073898,"domain_scores_codex":[0.861454,0.1290025,0.001667786,0.00338679,0.003833889,0.0006552336],"domain_scores_gemma":[0.8012044,0.1794292,0.005299112,0.007442371,0.00605154,0.0005734446],"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":[0.004357504,0.0006528167,0.1007932,0.002310196,0.02030274,0.0006713705,0.004724067,0.2968776,0.001164674,0.1102907,0.00710078,0.4507543],"study_design_scores_gemma":[0.0008309138,0.002080766,0.02993758,0.0007527531,0.003378025,0.0005339911,0.002001834,0.827388,0.0009829687,0.122422,0.009223741,0.0004674151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1004009,0.003135669,0.8901438,0.002113374,0.000297086,0.0007944954,0.0005661873,0.0007153245,0.001833111],"genre_scores_gemma":[0.4485343,0.002181994,0.5451941,0.0006806119,0.00009752411,0.001293652,0.0005223865,0.0002940231,0.001201381],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1118767,"threshold_uncertainty_score":0.5916679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3486952087988971,"score_gpt":0.4598331212879093,"score_spread":0.1111379124890122,"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."}}