{"id":"W4391932598","doi":"10.3233/shti231302","title":"Measuring and Managing Healthcare Supply and Demand in Real-Time","year":2024,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Institute for Work & Health; York University; Professional Engineers Ontario; University of Toronto","funders":"","keywords":"Health care; Key (lock); Business; Supply and demand; Demand management; Scheduling (production processes); On demand; Computer science; Operations management; Computer security; Economics","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":[0.002074633,0.0001471375,0.0004095424,0.0009223967,0.0007813263,0.00001695356,0.00005131717,0.0002654966,0.000003466416],"category_scores_gemma":[0.0002886901,0.0001301877,0.000007569095,0.0006912323,0.0002178682,0.0002663183,0.0001928236,0.0008132968,0.000005998219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021131,"about_ca_system_score_gemma":0.0002514446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000334277,"about_ca_topic_score_gemma":0.000936327,"domain_scores_codex":[0.9979852,0.0001803335,0.001071525,0.0001832985,0.00008853694,0.0004910576],"domain_scores_gemma":[0.999223,0.0003560185,0.0001138254,0.0001419645,0.00008090122,0.00008431549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004864048,0.00002846907,0.4564869,0.04142398,0.0000649006,0.00003037083,0.1733041,0.0002812487,0.000006285449,0.1591044,0.0008643333,0.1683565],"study_design_scores_gemma":[0.00407293,0.001299624,0.08623066,0.03831943,0.00003763383,0.0001896642,0.4381643,0.3526681,0.0000106679,0.05630025,0.02143633,0.001270426],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.874885,0.05564779,0.0004784098,0.06583276,0.000450585,0.001486317,0.00001540153,0.0003104604,0.0008933126],"genre_scores_gemma":[0.8277299,0.1585209,0.01231295,0.001109924,0.00003467776,0.0001613424,0.000008634936,0.00001608146,0.0001055669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3702562,"threshold_uncertainty_score":0.6009409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.105269433338103,"score_gpt":0.4382879108129706,"score_spread":0.3330184774748676,"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."}}