{"id":"W27510588","doi":"","title":"Computerized O.R. scheduling: is it an accurate predictor of surgical time?","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary General Hospital","funders":"","keywords":"Scheduling (production processes); Computer science; Surgical procedures; Medicine; Statistics; Surgery; Operations management; Mathematics; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001083396,0.0001322696,0.0003105925,0.0001032067,0.000414734,0.00001894996,0.0001797458,0.0002391421,0.001085673],"category_scores_gemma":[0.0001353096,0.0001162251,0.00005508668,0.0003291036,0.00004324891,0.0002548535,0.00005845008,0.0003194288,0.0001266345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000688833,"about_ca_system_score_gemma":0.0002351889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008936428,"about_ca_topic_score_gemma":0.00001706646,"domain_scores_codex":[0.9977062,0.0005276775,0.0007314991,0.0002789001,0.0002371958,0.0005185477],"domain_scores_gemma":[0.9985085,0.0002193398,0.0002118511,0.0003498695,0.0003792974,0.0003311536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005311913,0.004478443,0.4438264,0.002176825,0.0007703475,0.0002957398,0.05060196,0.0340269,0.0007847759,0.01671547,0.09645392,0.3445573],"study_design_scores_gemma":[0.008809026,0.0002585274,0.1774954,0.0002317046,0.00007697111,0.00002879359,0.001281621,0.5507002,0.0001244429,0.0002841896,0.2599231,0.0007860324],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681355,0.00006247603,0.00661718,0.01452023,0.0006205653,0.001922648,0.00005835283,0.0001610594,0.007901971],"genre_scores_gemma":[0.9801085,0.0002797998,0.009250346,0.001751186,0.0006352916,0.001007149,0.0001624674,0.00003512201,0.00677011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5166733,"threshold_uncertainty_score":0.9998274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.125800783036833,"score_gpt":0.4008847574502982,"score_spread":0.2750839744134652,"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."}}