{"id":"W2080035766","doi":"10.1109/services.2014.45","title":"Toward a Big Data Healthcare Analytics System: A Mathematical Modeling Perspective","year":2014,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; IBM (Canada)","funders":"Hospital for Sick Children; Canada Research Chairs","keywords":"Software deployment; Computer science; Big data; Analytics; Cloud computing; Health care; Intensive care; Perspective (graphical); Data analysis; Blocking (statistics); Data modeling; Computation; Data science; Data mining; Medicine; Artificial intelligence; Computer network; Database; Intensive care medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001688058,0.0009779452,0.0008173664,0.0007775808,0.0006648955,0.002749215,0.001451783,0.001835159,0.001799039],"category_scores_gemma":[0.004404615,0.0008051755,0.001007187,0.0009767513,0.001269282,0.003343981,0.001262072,0.002570703,0.0004064317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00189016,"about_ca_system_score_gemma":0.002384436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009036431,"about_ca_topic_score_gemma":0.005253334,"domain_scores_codex":[0.9994155,0.0002395091,0.00002731497,0.00008301642,0.0001678397,0.00006679373],"domain_scores_gemma":[0.9980358,0.001222623,0.000224669,0.00007552617,0.000347176,0.00009425424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002442806,0.00005529404,0.001268499,0.0001257272,0.00003974667,0.000103699,0.00009236822,0.879576,0.0009035501,0.1092952,0.001766184,0.006749315],"study_design_scores_gemma":[0.000004069542,0.00001235308,0.00007491914,0.00001205389,0.000004857129,0.00001462859,0.00002238026,0.9792523,0.000124977,0.01950448,0.0009668148,0.000006183724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01413245,0.0008761414,0.9700722,0.00725158,0.0001487859,0.0001091543,0.0002530351,0.0002047184,0.006951976],"genre_scores_gemma":[0.6100696,0.005939922,0.3696899,0.001543355,0.0006739487,0.0008460082,0.0005356881,0.0001804879,0.01052116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009036431,"threshold_uncertainty_score":0.01796764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3178515339084352,"score_gpt":0.3954830202245319,"score_spread":0.07763148631609668,"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."}}