{"id":"W7026499825","doi":"","title":"Advanced Stochastic Programming and Machine Learning
\\nModels for Healthcare Planning, Scheduling, and
\\nPrediction Problems","year":2024,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Material Selection and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scheduling (production processes); Stochastic programming; Stochastic modelling; Stochastic optimization; Linear programming; Dynamic programming; Service (business); Health care; Job shop scheduling","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003288935,0.001352124,0.001482797,0.0008102452,0.0006092998,0.001723631,0.001766367,0.001907321,0.00364178],"category_scores_gemma":[0.006381424,0.0007615642,0.001712178,0.001194232,0.001202641,0.001459365,0.001412269,0.003683535,0.0003568124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002242071,"about_ca_system_score_gemma":0.00283349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0133891,"about_ca_topic_score_gemma":0.01123378,"domain_scores_codex":[0.9982176,0.001023347,0.00007777625,0.0002652415,0.0002484187,0.0001674715],"domain_scores_gemma":[0.9942645,0.004664924,0.000444516,0.0001624996,0.0003158045,0.0001477582],"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":[0.000009894414,0.00002248843,0.0002688653,0.00004247509,0.00002184279,0.00002737315,0.00001720012,0.9527858,0.00007926323,0.04057091,0.0007737033,0.005380206],"study_design_scores_gemma":[0.000003641567,0.000006389034,0.00004009922,0.000005410948,0.000002534419,0.000004137118,0.000004496987,0.9804512,0.00002964792,0.01899677,0.0004528011,0.000002860944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007627385,0.0005633421,0.9869681,0.001413048,0.0001160256,0.00005097355,0.0002913931,0.00009705476,0.002872705],"genre_scores_gemma":[0.5921572,0.004515087,0.3842268,0.0010716,0.0009067557,0.0009641932,0.001228898,0.0001823989,0.01474711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0133891,"threshold_uncertainty_score":0.02662235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03793973722100782,"score_gpt":0.2972362077039553,"score_spread":0.2592964704829475,"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."}}