{"id":"W2000674974","doi":"10.1108/09564230410532493","title":"Outpatient appointment scheduling with urgent clients in a dynamic, multi‐period environment","year":2004,"lang":"en","type":"article","venue":"International Journal of Service Industry Management","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Brock University","funders":"","keywords":"Scheduling (production processes); Waiting period; Operations management; Computer science; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00145478,0.0005071087,0.001052369,0.0003494021,0.0008864678,0.001183579,0.001373859,0.001242048,0.002833404],"category_scores_gemma":[0.003420441,0.0006682293,0.0005786438,0.0006830791,0.0005322496,0.0008876505,0.0007953626,0.0009655489,0.0002605874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001250039,"about_ca_system_score_gemma":0.001442972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01239329,"about_ca_topic_score_gemma":0.01090757,"domain_scores_codex":[0.9989027,0.0004065163,0.00003360185,0.0001685684,0.0001386624,0.000350046],"domain_scores_gemma":[0.9965779,0.002134794,0.0005117836,0.0001377182,0.0001531822,0.0004846813],"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":[0.001627227,0.0004218546,0.00480039,0.0001009167,0.00006714414,0.000622862,0.0001580712,0.9729974,0.003193243,0.002364366,0.001348228,0.01229821],"study_design_scores_gemma":[0.0001290688,0.0003601591,0.00374031,0.000005039622,0.00002236525,0.0001425982,0.0002435158,0.993085,0.0005004206,0.001324604,0.0004232479,0.00002356746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9485505,0.0002115308,0.04715288,0.0005172027,0.00005630339,0.00009122006,0.0002930028,0.0001635653,0.002963746],"genre_scores_gemma":[0.9926242,0.00008932224,0.006096667,0.00002783818,0.00002884802,0.00002877329,0.00008792333,0.00001684842,0.0009993685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01239329,"threshold_uncertainty_score":0.02464229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.046174170512704,"score_gpt":0.3773566917002346,"score_spread":0.3311825211875306,"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."}}