{"id":"W2278594462","doi":"10.2196/iproc.4772","title":"Predictive Modeling of Emergency Hospital Transport Using Medical Alert Pattern Data: Retrospective Cohort Study","year":2015,"lang":"en","type":"article","venue":"Iproceedings","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retrospective cohort study; Medical emergency; Emergency medicine; Medicine; Cohort; Emergency department; Computer science; Internal medicine; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008887564,0.0002731693,0.000715433,0.0001100892,0.000105416,0.000003994638,0.0003506046,0.0001390331,0.0001254966],"category_scores_gemma":[0.0006060477,0.0002343256,0.0001091921,0.0003909346,0.0000903649,0.0004090705,0.0002127664,0.0003627332,0.000003906732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001240583,"about_ca_system_score_gemma":0.0002005892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000726455,"about_ca_topic_score_gemma":0.00003778872,"domain_scores_codex":[0.9967304,0.00001190851,0.0006985532,0.0006976794,0.001519684,0.0003418099],"domain_scores_gemma":[0.9978869,0.000008341109,0.0001692446,0.0003617669,0.001265295,0.0003084614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009854843,0.0006303291,0.9860466,0.00007549246,0.0006375717,0.00005317968,0.008865654,0.00001738625,0.00006547773,0.000009364342,0.003345887,0.0001545515],"study_design_scores_gemma":[0.004728799,0.004243661,0.7795858,0.0006720833,0.002743271,0.00006134577,0.05666728,0.1496963,0.000212592,0.0003182794,0.0002076015,0.0008629355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903683,0.0006089481,0.003109096,0.0002954433,0.001162174,0.0009234811,0.00008753399,0.00009765993,0.003347384],"genre_scores_gemma":[0.9985507,0.0003930632,0.0001514425,0.00004906645,0.0006755787,0.00002799125,0.00006017019,0.00004169108,0.0000503602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2064607,"threshold_uncertainty_score":0.9555519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06620028919880212,"score_gpt":0.3378118021171054,"score_spread":0.2716115129183033,"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."}}