{"id":"W4312602176","doi":"10.2139/ssrn.4278297","title":"Surgical Scheduling to Smooth Demand for Resources","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Scheduling (production processes); Business; Operations management; Computer science; Operations research; Economics; Engineering","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":["sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006416089,0.0001135965,0.0001980422,0.0001763854,0.005080616,0.00002816511,0.0002224364,0.00007920792,0.0002872079],"category_scores_gemma":[0.0002525147,0.0001047206,0.00008492675,0.00032124,0.00001105618,0.00008744633,0.00008802512,0.002773472,0.00002660755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014811,"about_ca_system_score_gemma":0.004090745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008780502,"about_ca_topic_score_gemma":0.0004737964,"domain_scores_codex":[0.9961329,0.000675269,0.0005250044,0.0002233368,0.0002914731,0.002152093],"domain_scores_gemma":[0.9989892,0.0002956048,0.0001588987,0.0001484171,0.0002168802,0.0001909926],"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":[0.001731272,0.0003217353,0.01857671,0.0001224804,0.0002353513,0.00001857488,0.01637709,0.3279063,0.0002673177,0.5820899,0.003539728,0.04881361],"study_design_scores_gemma":[0.005063,0.002585065,0.0007771493,0.0001052384,0.00006756096,0.0003048347,0.06602549,0.02912758,0.000008273488,0.05349167,0.8417969,0.0006472929],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8368731,0.001375765,0.1404039,0.01850888,0.0007783209,0.001082942,0.00001998451,0.00006923305,0.0008879417],"genre_scores_gemma":[0.9856092,0.0004491927,0.005765388,0.001204284,0.001035619,0.0003515156,0.00002453018,0.00004345479,0.005516799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8382571,"threshold_uncertainty_score":0.9995272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03574154398966074,"score_gpt":0.3899512567160165,"score_spread":0.3542097127263558,"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."}}