{"id":"W2009097495","doi":"10.1109/istas.2013.6613120","title":"Wearable monitors on babies: Big data saving little people","year":2013,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Context (archaeology); Intensive care; Big data; Wearable computer; Health care; Ambulatory care; Neonatal intensive care unit; Cloud computing; Medical emergency; Medicine; Computer science; Pediatrics; Intensive care medicine; Geography; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001655516,0.0001112324,0.0001928336,0.0001184131,0.0001186477,0.00001573325,0.000213733,0.000166317,0.0004236423],"category_scores_gemma":[0.0002712991,0.00008753948,0.00002348005,0.0002204772,0.00003220685,0.0001278315,0.0001351993,0.0003288603,0.001435801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004852611,"about_ca_system_score_gemma":0.00006956538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002402333,"about_ca_topic_score_gemma":0.00009818902,"domain_scores_codex":[0.9989949,0.00002477383,0.0001963393,0.0002977646,0.0001760987,0.0003100563],"domain_scores_gemma":[0.9986371,0.0001306123,0.00003589093,0.0009974968,0.0000613274,0.0001376212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002942599,0.0001750536,0.6908481,0.0001561524,0.0000440305,0.00001113407,0.000355813,0.000002192244,0.001425853,0.0002289796,0.02200516,0.2847181],"study_design_scores_gemma":[0.002159074,0.001982774,0.8778201,0.001429227,0.00009288827,0.00007177343,0.005101759,0.001636635,0.02030957,0.0007729351,0.08792978,0.0006935152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803438,0.000195263,0.0000763258,0.00434636,0.001075947,0.0003661798,0.000003985481,0.0003667762,0.01322541],"genre_scores_gemma":[0.9936818,0.0001004639,0.001112693,0.0004028874,0.0005346672,0.00002819159,0.00002578297,0.00001814836,0.004095375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2840246,"threshold_uncertainty_score":0.9993417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109808741301931,"score_gpt":0.3296419740388726,"score_spread":0.2198332327369416,"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."}}