{"id":"W2396085405","doi":"10.1515/cclm-2015-0537","title":"Early prediction of gestational diabetes: a practical model combining clinical and biochemical markers","year":2015,"lang":"en","type":"article","venue":"Clinical Chemistry and Laboratory Medicine (CCLM)","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Medicine; Gestational diabetes; Glycated hemoglobin; Obstetrics; Pregnancy; Logistic regression; Sex hormone-binding globulin; Diabetes mellitus; Internal medicine; Gestation; Gynecology; Type 2 diabetes; Endocrinology; Hormone; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002883894,0.0001916475,0.0006031917,0.00004055284,0.00004670423,0.00001294558,0.00007602591,0.0002836138,0.00005850401],"category_scores_gemma":[0.008441799,0.0001593013,0.00006848607,0.000206809,0.001666743,0.000129296,0.00009275888,0.0007051986,0.000003842289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002589737,"about_ca_system_score_gemma":0.0004985614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002584864,"about_ca_topic_score_gemma":9.35154e-8,"domain_scores_codex":[0.9973319,0.000164397,0.001056769,0.0004966147,0.0006574404,0.000292928],"domain_scores_gemma":[0.9964936,0.001228912,0.0002219548,0.0002607248,0.0006773054,0.00111754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002203882,0.0013023,0.8651651,0.001668048,0.0005932692,0.00007682999,0.0003052723,0.00001534673,0.009656036,0.0006354345,0.1161943,0.002184232],"study_design_scores_gemma":[0.03189956,0.006066941,0.8768274,0.001693844,0.001211407,0.00003309222,0.00208466,0.059983,0.00255711,0.00416954,0.01283977,0.0006337074],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930583,0.0005816655,0.0003033765,0.003831812,0.0001094775,0.000265432,0.00008145584,0.00004087481,0.00172766],"genre_scores_gemma":[0.9940556,0.0006001628,0.003257633,0.001039649,0.0004619361,0.00002790756,0.0001805393,0.00002145146,0.0003550742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1033545,"threshold_uncertainty_score":0.9999105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09971500306439789,"score_gpt":0.4026453702270423,"score_spread":0.3029303671626444,"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."}}