{"id":"W4311768425","doi":"10.1007/s10696-022-09478-3","title":"Analytics and Optimization in Healthcare Management","year":2022,"lang":"en","type":"article","venue":"Flexible Services and Manufacturing Journal","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Analytics; Computer science; Health care; Data science","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":[0.000801745,0.0001083649,0.0002347527,0.0003387573,0.0004112972,0.00007111688,0.00005845295,0.00004146908,0.0001004167],"category_scores_gemma":[0.000001452993,0.00009732934,0.00002497986,0.0001270955,0.0000100182,0.000114703,0.000116456,0.0004654099,5.324452e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001637184,"about_ca_system_score_gemma":0.0001089081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001414985,"about_ca_topic_score_gemma":0.0001325964,"domain_scores_codex":[0.9987422,0.0001064556,0.0003648052,0.0001936013,0.0002813404,0.000311557],"domain_scores_gemma":[0.9993802,0.00001472398,0.0001218316,0.0001159942,0.00002847299,0.0003387953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00139465,0.0006826405,0.1972476,0.03453237,0.0004900815,0.002665118,0.01235959,0.1925153,0.00001524689,0.007246525,0.001720464,0.5491304],"study_design_scores_gemma":[0.01106495,0.00267008,0.4758642,0.001765563,0.0001593293,0.01300724,0.02597383,0.1020488,0.00009826005,0.003007255,0.3633796,0.0009608876],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564496,0.003717229,0.001126918,0.03608286,0.0004926937,0.0006314532,0.0000133515,0.00005739983,0.001428495],"genre_scores_gemma":[0.9901581,0.002532447,0.002650199,0.003979414,0.000163663,0.00001314811,0.00001685766,0.00001776068,0.0004683946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5481695,"threshold_uncertainty_score":0.3968975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02153227906539908,"score_gpt":0.2928210598385378,"score_spread":0.2712887807731387,"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."}}