{"id":"W2789142274","doi":"10.1017/s0269964818000402","title":"ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH","year":2018,"lang":"en","type":"article","venue":"Probability in the Engineering and Informational Sciences","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Notice; Schedule; Markov decision process; Computer science; Dynamic programming; Quality (philosophy); Capacity planning; Operations research; Scheduling (production processes); Space (punctuation); Process (computing); Mathematical optimization; Markov process; Operations management; Mathematics; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003019626,0.00008705464,0.00009977173,0.00009307833,0.0009852712,0.00005065148,0.000126306,0.00006664205,0.000002946618],"category_scores_gemma":[0.0007343578,0.00005773866,0.0000164059,0.0003126066,0.0001565057,0.0006930432,0.00001680425,0.0001457271,9.233585e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009774131,"about_ca_system_score_gemma":0.0001041178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007025808,"about_ca_topic_score_gemma":0.00004228293,"domain_scores_codex":[0.9988996,0.0001204599,0.0003990264,0.0001592246,0.0001722541,0.0002494123],"domain_scores_gemma":[0.9991587,0.0004472856,0.00007871957,0.0001098435,0.0001626515,0.00004277118],"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":[0.00004270269,0.0004081497,0.01548634,0.0009835591,0.00001106852,3.746198e-8,0.1208655,0.7999911,0.00003051926,0.05025978,0.00002238361,0.0118989],"study_design_scores_gemma":[0.0002061225,0.0002753859,0.01173772,0.00005725469,0.000003050232,0.000001217201,0.005457899,0.9802648,7.390934e-7,0.001564402,0.0003602648,0.00007116347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684707,0.00001764222,0.02883442,0.0009166836,0.00009488939,0.001373292,0.00002417454,0.00005575271,0.0002124753],"genre_scores_gemma":[0.777508,0.000002390209,0.2217266,0.0001139287,0.00006561032,0.0004616219,0.000113107,0.000003389153,0.00000533133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1928922,"threshold_uncertainty_score":0.7578009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09656401437862992,"score_gpt":0.4091299141877374,"score_spread":0.3125658998091075,"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."}}