{"id":"W2127417141","doi":"10.1109/compsac.2009.122","title":"A Survey of Physiological Monitoring Data Models to Support the Service of Critical Care","year":2009,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Health Canada; Canada Research Chairs; Ontario Centres of Excellence","keywords":"Service (business); Computer science; Data collection; Architecture; Intensive care unit; Data science; Process management; Medicine; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003675237,0.000080429,0.000258636,0.00004302009,0.00003863014,0.000001590182,0.0003381264,0.0001296624,0.00001549142],"category_scores_gemma":[0.0003998906,0.00004967896,0.00002017894,0.0002891212,0.00005025044,0.00005856746,0.0001479694,0.0002038803,0.000004826644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000151132,"about_ca_system_score_gemma":0.0000897322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027128,"about_ca_topic_score_gemma":0.00005926067,"domain_scores_codex":[0.9990605,0.00007399476,0.0002784433,0.0002079505,0.0001882995,0.0001908535],"domain_scores_gemma":[0.9984557,0.0001986493,0.00003219832,0.0008091742,0.0004186168,0.00008568518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001122571,0.001327477,0.7776073,0.001972228,0.0001032475,0.00005618329,0.008530124,0.000327556,0.04506161,0.004707804,0.001637189,0.1575467],"study_design_scores_gemma":[0.0003873341,0.002337219,0.9686077,0.000193799,0.00004968277,0.000008475018,0.002602935,0.0009204444,0.02446163,0.0002689839,0.0000408113,0.0001209727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961607,0.0001359566,0.0002886269,0.002393715,0.0001332491,0.0002239819,0.00005132707,0.00005474185,0.0005576686],"genre_scores_gemma":[0.997784,0.00000908345,0.001766783,0.0003070037,0.0000669053,0.000003182066,0.00004934718,0.000004492325,0.000009251635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1910004,"threshold_uncertainty_score":0.2025849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4565959831513244,"score_gpt":0.4659792931122351,"score_spread":0.009383309960910746,"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."}}