{"id":"W2116021647","doi":"10.1287/opre.1120.1053","title":"Technical Note—A Sampling-Based Approach to Appointment Scheduling","year":2012,"lang":"en","type":"article","venue":"Operations Research","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Western University","funders":"","keywords":"Convexity; Scheduling (production processes); Computer science; Mathematical optimization; Random variable; Sequence (biology); Operations research; Mathematics; Statistics","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":[0.007187024,0.001170393,0.001503565,0.001408087,0.001116529,0.001975023,0.003979345,0.001398047,0.007457529],"category_scores_gemma":[0.02071195,0.0009351341,0.00186821,0.002223104,0.0016223,0.002585315,0.002889942,0.003826435,0.001252782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736976,"about_ca_system_score_gemma":0.002482091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004710319,"about_ca_topic_score_gemma":0.004311928,"domain_scores_codex":[0.9940121,0.003095923,0.000207899,0.0007280608,0.001667618,0.0002885005],"domain_scores_gemma":[0.9903442,0.007272317,0.000516224,0.0007438929,0.0007801711,0.0003431383],"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":[0.0001995057,0.0002275556,0.001647173,0.0003183477,0.0001254635,0.0002696894,0.0001818566,0.6714125,0.002651787,0.234676,0.00832606,0.07996406],"study_design_scores_gemma":[0.00002566573,0.00005952841,0.0001911593,0.00002205366,0.00001753562,0.00008600702,0.00001876789,0.9481332,0.0003941263,0.04703582,0.004000789,0.00001528481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008402508,0.0001986008,0.99695,0.0002660526,0.00007686218,0.00007847702,0.00004928524,0.00006905439,0.001471419],"genre_scores_gemma":[0.1776945,0.00176431,0.8115542,0.000690786,0.001281184,0.000690248,0.0004263023,0.0001986451,0.005699838],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007457529,"threshold_uncertainty_score":0.03800905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3663674088889178,"score_gpt":0.568893804272135,"score_spread":0.2025263953832172,"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."}}