{"id":"W2945667677","doi":"10.1007/s10916-019-1337-y","title":"Decision Tree Predictive Learner-Based Approach for False Alarm Detection in ICU","year":2019,"lang":"en","type":"article","venue":"Journal of Medical Systems","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Decision tree; Health informatics; Computer science; ALARM; False alarm; Decision tree learning; Tree (set theory); Machine learning; Artificial intelligence; Data mining; Medicine; Nursing; Public health; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.002746834,0.0001005241,0.00047355,0.0003300815,0.00003198192,0.000007494498,0.0001479942,0.0005325198,0.00001066231],"category_scores_gemma":[0.001409926,0.00007038665,0.0001190394,0.0002153285,0.00003406535,0.00006334238,0.00001459936,0.000816067,0.00000590589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002288109,"about_ca_system_score_gemma":0.0002879294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005821889,"about_ca_topic_score_gemma":0.000009259099,"domain_scores_codex":[0.9977427,0.0001221418,0.0007447966,0.0001499109,0.001019808,0.0002206371],"domain_scores_gemma":[0.9986399,0.0004476484,0.0003146245,0.000149704,0.0001908511,0.0002572653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006821465,0.001282364,0.5206161,0.002751598,0.0002142018,0.0002752578,0.0005183328,0.002908401,0.002381332,0.0001360637,0.0009253016,0.4611696],"study_design_scores_gemma":[0.05558547,0.03068447,0.111119,0.02069822,0.0003609,0.003230572,0.00690125,0.7312196,0.007944474,0.0002514943,0.03129696,0.0007076672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8804316,0.000741683,0.1152166,0.0006657816,0.002069102,0.0007223843,0.000001512876,0.00002623398,0.0001250984],"genre_scores_gemma":[0.998431,0.00003912969,0.0007831176,0.00005656899,0.0006028955,0.00002565661,0.000002694069,0.00001368927,0.00004525402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7283112,"threshold_uncertainty_score":0.4107281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357528384279305,"score_gpt":0.3329877754827338,"score_spread":0.2994124916399408,"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."}}