{"id":"W4411395743","doi":"10.1016/j.ordal.2025.200480","title":"Robust appointment scheduling for random service times using min-max optimization","year":2025,"lang":"en","type":"article","venue":"Operations Research Data Analytics and Logistics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scheduling (production processes); Computer science; Mathematical optimization; Operations research; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004229725,0.0001723367,0.0003168877,0.000425724,0.004335787,0.0003183116,0.00042766,0.000247945,0.0001454047],"category_scores_gemma":[0.004605889,0.0001570488,0.00002690129,0.001077044,0.0001274744,0.0003762625,0.00050262,0.0005834532,0.00001241645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002362635,"about_ca_system_score_gemma":0.002090392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001263853,"about_ca_topic_score_gemma":0.00205962,"domain_scores_codex":[0.9970942,0.000647389,0.0007747802,0.0005860475,0.0003276946,0.0005699575],"domain_scores_gemma":[0.9947205,0.001260143,0.00006180041,0.0009314176,0.002854017,0.0001721782],"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":[0.00005267739,0.00006968367,0.0002158617,0.0002583522,0.00005645116,8.490726e-7,0.0002028131,0.9674914,0.00004335978,0.02919649,0.001911553,0.0005004773],"study_design_scores_gemma":[0.001194023,0.00004384559,0.00001810682,0.0002197766,0.00009060093,6.517421e-7,0.002149622,0.9906232,0.000005876936,0.0002432735,0.005270056,0.0001409222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001206108,0.0003461521,0.9867175,0.00775931,0.000230248,0.001956924,0.0007745103,0.0000375489,0.0009716583],"genre_scores_gemma":[0.07850714,0.001568281,0.9076759,0.001275694,0.0003895475,0.0002559129,0.006877374,0.00004272256,0.003407488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0790417,"threshold_uncertainty_score":0.9969605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5803760554017239,"score_gpt":0.5555374177115556,"score_spread":0.02483863769016825,"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."}}