{"id":"W4399134520","doi":"10.2139/ssrn.4838943","title":"Multi-Operator Driven Iterated Tabu Search for Collaborative Operating Room Scheduling","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Tabu search; Iterated function; Operator (biology); Scheduling (production processes); Computer science; Mathematical optimization; Mathematics; Chemistry","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":[0.002669148,0.0009559382,0.002225793,0.001046007,0.0008016469,0.001245752,0.002647542,0.002510758,0.004670469],"category_scores_gemma":[0.007917922,0.00112946,0.001448793,0.001331959,0.000859733,0.001283873,0.001604053,0.001706107,0.0006021351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001124918,"about_ca_system_score_gemma":0.002539646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01239225,"about_ca_topic_score_gemma":0.008370509,"domain_scores_codex":[0.9986481,0.0006761616,0.00004578374,0.0001417643,0.0002771655,0.0002109864],"domain_scores_gemma":[0.9960216,0.00294167,0.0002467933,0.0001754936,0.0004195679,0.000194812],"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":[0.00007856006,0.00005305141,0.0001775684,0.00002448439,0.00002628861,0.00002376478,0.00002657367,0.9877294,0.0002244971,0.001171447,0.0004989081,0.009965528],"study_design_scores_gemma":[0.000009470252,0.00001426913,0.00002307204,0.000001739544,0.000002667109,0.00000221686,0.000003942935,0.9993615,0.00003970301,0.0005019754,0.00003801553,0.000001480488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06562653,0.000381787,0.9264377,0.0003368639,0.0001108439,0.0001722898,0.0001857547,0.0007596428,0.005988545],"genre_scores_gemma":[0.7258391,0.0001087468,0.2696418,0.0001607373,0.00007667016,0.0004017867,0.0002577219,0.0002621389,0.003251324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01239225,"threshold_uncertainty_score":0.02464026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07198089195609775,"score_gpt":0.4351528256332932,"score_spread":0.3631719336771955,"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."}}