{"id":"W2913699606","doi":"10.1007/978-3-030-04506-7_4","title":"Healthcare Analytics Applications","year":2019,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in health care management and economics","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Health care; Analytics; Data science; Computer science; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001168438,0.001211482,0.0005853192,0.002241432,0.0007084399,0.004849143,0.00132808,0.00126786,0.1642236],"category_scores_gemma":[0.003569151,0.0004197069,0.000678386,0.00282267,0.0003518552,0.002627257,0.00295266,0.001241565,0.1088823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005339839,"about_ca_system_score_gemma":0.0009386788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001047174,"about_ca_topic_score_gemma":0.001318391,"domain_scores_codex":[0.9990271,0.000211954,0.00006623978,0.0001426689,0.000486436,0.00006571547],"domain_scores_gemma":[0.998953,0.0003404543,0.00003741745,0.0002315213,0.0003419057,0.00009572905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003305669,0.00005266774,0.0002999038,0.000323759,0.00002033869,0.00009650878,0.0001147487,0.0005071511,0.00100907,0.02945911,0.556829,0.4112546],"study_design_scores_gemma":[0.00000836547,0.00001301664,0.000318717,0.0001460545,0.000009200894,0.0001509807,0.00006746186,0.002056621,0.0006342783,0.02124847,0.9753388,0.000008152783],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002107,0.01302074,0.08672559,0.01164747,0.004265086,0.000466395,0.006501724,0.01156035,0.8637056],"genre_scores_gemma":[0.03828523,0.0189926,0.06483189,0.007928686,0.003850676,0.0005216242,0.01917754,0.001871911,0.8445398],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1642236,"threshold_uncertainty_score":0.5493827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07924098111654782,"score_gpt":0.3853999124130985,"score_spread":0.3061589312965506,"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."}}