{"id":"W3173854027","doi":"10.1002/nav.22011","title":"Business analytics in service operations—Lessons from healthcare operations","year":2021,"lang":"en","type":"article","venue":"Naval Research Logistics (NRL)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Business analytics; Analytics; Computer science; Data science; Business intelligence; Knowledge management; Management science; Process management; Business model; Business; Business analysis; Engineering; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009538095,0.0006175764,0.0005028591,0.002918133,0.001880144,0.01016379,0.001446266,0.002309638,0.002807351],"category_scores_gemma":[0.02095365,0.0002988657,0.0005996738,0.003933645,0.008896282,0.0100648,0.003602904,0.004327206,0.0004978791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004035775,"about_ca_system_score_gemma":0.006399626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009430631,"about_ca_topic_score_gemma":0.005042172,"domain_scores_codex":[0.9954244,0.00341802,0.000159393,0.0001606983,0.000492514,0.0003450403],"domain_scores_gemma":[0.9779743,0.01704968,0.0007483582,0.0008788884,0.002014814,0.001333974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009982133,0.000211403,0.009903635,0.0004688723,0.00003581586,0.0007329431,0.01003233,0.009268138,0.000194287,0.8376576,0.01976057,0.1116346],"study_design_scores_gemma":[0.00003445298,0.00008459384,0.004574819,0.001164478,0.00001618336,0.0002874237,0.02123734,0.02377298,0.0003405059,0.8757815,0.07265393,0.00005178377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.125946,0.03814981,0.1393595,0.5610897,0.001604153,0.0003147102,0.0004541202,0.0004291044,0.1326529],"genre_scores_gemma":[0.9439075,0.01950649,0.02713227,0.005156769,0.0009767475,0.0001334156,0.0001643902,0.00008637413,0.002936212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01016379,"threshold_uncertainty_score":0.05044287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4203332503718576,"score_gpt":0.4656265872508525,"score_spread":0.04529333687899495,"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."}}