{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006852846,0.0006478069,0.0004417537,0.0009917713,0.0003335121,0.001006857,0.001085392,0.0006931542,0.0009228587],"category_scores_gemma":[0.01456239,0.0006333762,0.001346314,0.000911947,0.0003019716,0.0006347056,0.0007115344,0.001405133,0.0003297947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005166289,"about_ca_system_score_gemma":0.0008916457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01384604,"about_ca_topic_score_gemma":0.007367258,"domain_scores_codex":[0.9986346,0.0005408069,0.0001333393,0.0003736056,0.0001922178,0.0001252895],"domain_scores_gemma":[0.9922186,0.003332076,0.001337072,0.001987346,0.0007612055,0.0003636443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003321088,0.0001638678,0.9948644,0.00000760586,0.0002399156,0.00009301656,0.00006716666,0.001942451,0.0001147978,0.00003949074,0.0002371811,0.001898075],"study_design_scores_gemma":[0.00008652871,0.0007780398,0.8921195,0.00003040052,0.0003962248,0.000509597,0.0005049501,0.1041068,0.0004675812,0.0002727936,0.000689104,0.00003843718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978337,0.00005859955,0.001261687,0.00003840693,0.000008273256,0.00002672388,0.0006803086,0.00001227505,0.00008001363],"genre_scores_gemma":[0.9974304,0.00009150603,0.0009292485,0.00001371119,0.00001015509,0.00002743412,0.00137227,0.000006641108,0.0001188413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01384604,"threshold_uncertainty_score":0.03624177,"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."}}