{"id":"W2142819178","doi":"10.1287/ited.2013.0119","title":"The Appointment Scheduling Game","year":2014,"lang":"en","type":"article","venue":"INFORMS Transactions on Education","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Operations research; Health care; Markov decision process; Operations management; Markov process; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008328434,0.0008844289,0.0004922014,0.0003857538,0.0009235149,0.001821175,0.00111071,0.001471724,0.03024538],"category_scores_gemma":[0.003386753,0.0002434716,0.0005799858,0.0003101001,0.0009313981,0.001779546,0.001967364,0.001560502,0.002751475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129444,"about_ca_system_score_gemma":0.00170976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003313098,"about_ca_topic_score_gemma":0.003920039,"domain_scores_codex":[0.9988667,0.0005504134,0.00005240091,0.0001271461,0.000226188,0.0001771909],"domain_scores_gemma":[0.9989945,0.0006132537,0.00005590815,0.00005205769,0.00007840867,0.0002059139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004893784,0.0007872914,0.001708028,0.0003075956,0.00004084132,0.0005714352,0.001064244,0.05736456,0.002765274,0.7407874,0.07735102,0.1167629],"study_design_scores_gemma":[0.0003442713,0.0007158806,0.001160514,0.000168863,0.00002651816,0.0005664114,0.001045409,0.2315465,0.001534635,0.3197028,0.4431027,0.0000854691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06239774,0.001108455,0.3715623,0.01005108,0.001187029,0.001775768,0.001886648,0.001380421,0.5486505],"genre_scores_gemma":[0.6168157,0.001684184,0.2121351,0.003339287,0.0003490994,0.00220804,0.001907318,0.0002342954,0.161327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03024538,"threshold_uncertainty_score":0.1011808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02831239539112205,"score_gpt":0.3882065085429044,"score_spread":0.3598941131517823,"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."}}