{"id":"W7132987834","doi":"","title":"Magnetic Resonance Imaging Schedule Optimization at JDMI","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Medical imaging; Scheduling (production processes); Schedule; Mri scan; Flexibility (engineering)","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":[0.0007038802,0.0007175663,0.0005291515,0.0004134135,0.0005525532,0.001102584,0.0005536033,0.0005364599,0.008970758],"category_scores_gemma":[0.002101264,0.0002740191,0.0004581563,0.0005919811,0.0002735834,0.0005047866,0.0006125461,0.0007929901,0.0008952206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002014818,"about_ca_system_score_gemma":0.004082424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01877473,"about_ca_topic_score_gemma":0.01987757,"domain_scores_codex":[0.9995723,0.0001195173,0.000008614488,0.00008688136,0.00008044114,0.0001322595],"domain_scores_gemma":[0.9993672,0.0002758672,0.00006366865,0.00004113074,0.0001199744,0.0001322922],"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":[0.0002006331,0.0001456812,0.001048661,0.00008742071,0.00002085605,0.00007198051,0.00005965465,0.9292338,0.002368577,0.008662616,0.01004013,0.04806003],"study_design_scores_gemma":[0.00002877957,0.0001086513,0.0007065561,0.00001037899,0.000008762101,0.00002438822,0.0001011301,0.9883554,0.001074128,0.004921499,0.004652987,0.000007375566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3766719,0.001432,0.5205157,0.003758466,0.000451335,0.0005858957,0.002317174,0.001513647,0.09275389],"genre_scores_gemma":[0.8226167,0.0005148382,0.155699,0.0002045352,0.00007457358,0.0002095972,0.001194673,0.0002362688,0.01924999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01877473,"threshold_uncertainty_score":0.03733093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04433965299030817,"score_gpt":0.4334014850862734,"score_spread":0.3890618320959652,"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."}}