{"id":"W2486988927","doi":"10.4018/978-1-4666-9432-3.ch005","title":"A Predictive Analytic Model for Maternal Morbidity","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in healthcare information systems and administration book series","topic":"Maternal and Neonatal Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Bayesian network; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007083098,0.0003963318,0.0007056451,0.000255755,0.000473636,0.00004906228,0.0001402571,0.0006129291,0.00003185918],"category_scores_gemma":[0.00005010552,0.0003603463,0.00006588176,0.00003913293,0.000101227,0.004048609,0.00006218595,0.000632184,0.00004490728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644032,"about_ca_system_score_gemma":0.001389358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005522533,"about_ca_topic_score_gemma":0.002168814,"domain_scores_codex":[0.9967429,0.00008524353,0.001922252,0.00031336,0.0004962405,0.000439984],"domain_scores_gemma":[0.9969439,0.0001588016,0.00131929,0.000269172,0.0009887234,0.0003201378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00206014,0.000009748132,0.002377961,0.02595872,0.00003227205,0.000009786124,0.002809845,0.0009000904,2.183283e-7,0.9591312,0.002121882,0.004588073],"study_design_scores_gemma":[0.0009091861,0.0007903993,0.0003484574,0.003478694,0.00002374646,0.00004801605,0.00163441,0.02038807,0.000002015931,0.02181803,0.9500764,0.0004825818],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00482318,0.1558029,0.02357743,0.01676972,0.01426924,0.03864754,0.04228626,0.001315494,0.7025083],"genre_scores_gemma":[0.4637316,0.03054278,0.0005927364,0.002120267,0.001133718,0.002515216,0.00265526,0.0001087065,0.4965997],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9479545,"threshold_uncertainty_score":0.9998848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08546913784404657,"score_gpt":0.4070387273802971,"score_spread":0.3215695895362505,"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."}}