{"id":"W2129613212","doi":"10.1111/j.1399-5448.2011.00795.x","title":"Validation of classification algorithms for childhood diabetes identified from administrative data","year":2011,"lang":"en","type":"article","venue":"Pediatric Diabetes","topic":"Diabetes and associated disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; Provincial Health Services Authority; Kruger (Canada); University of British Columbia; Ministry of Health; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Algorithm; Type 2 diabetes; Diabetes mellitus; Type 1 diabetes; Epidemiology; Pediatrics; Data mining; Database; Internal medicine; Endocrinology; Computer science","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":[0.03435404,0.00146211,0.001056409,0.004383535,0.0007688573,0.002157844,0.001924739,0.001508312,0.0008574855],"category_scores_gemma":[0.07847387,0.000386784,0.001214147,0.001732323,0.0006971197,0.001167572,0.001383505,0.001362653,0.0004982869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001941298,"about_ca_system_score_gemma":0.002834485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00879884,"about_ca_topic_score_gemma":0.004911445,"domain_scores_codex":[0.9859602,0.007310331,0.001995263,0.001960617,0.002185895,0.0005875907],"domain_scores_gemma":[0.9222428,0.05284688,0.005848283,0.003726009,0.01468972,0.0006463425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001817746,0.001024754,0.7733949,0.0003253483,0.001053492,0.0001834408,0.0004872326,0.07579003,0.001976172,0.001071,0.003383306,0.1394926],"study_design_scores_gemma":[0.0004246985,0.0007212028,0.1623279,0.0002471277,0.0003256292,0.0003753035,0.0004287247,0.8230653,0.007384955,0.002170211,0.002465026,0.00006392688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8799655,0.0007314295,0.1097262,0.0006395412,0.0001794242,0.001868992,0.002769623,0.001089214,0.003029997],"genre_scores_gemma":[0.8644874,0.0001990033,0.1295665,0.0002180833,0.00004080582,0.0008483416,0.004172953,0.00006330644,0.000403667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03435404,"threshold_uncertainty_score":0.1816837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06028097476215149,"score_gpt":0.2848590601494373,"score_spread":0.2245780853872858,"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."}}