{"id":"W6926370614","doi":"10.25384/sage.21385499","title":"sj-docx-1-mpp-10.1177_23814683221134098 – Supplemental material for Optimal Planning of Health Services through Genetic Algorithm and Discrete Event Simulation: A Proposed Model and Its Application to Stroke Rehabilitation Care","year":2022,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Clostridium difficile and Clostridium perfringens research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics; University of Alberta; University of Calgary","funders":"","keywords":"Rehabilitation; Genetic algorithm; Event (particle physics); Stroke (engine); Health care; Health services","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001475654,0.0008747148,0.0009084243,0.002237188,0.0006661047,0.002735533,0.002509603,0.002341128,0.8928131],"category_scores_gemma":[0.01959733,0.001062091,0.0008739584,0.003593089,0.0003600277,0.001862415,0.001410064,0.001428576,0.5245543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0018945,"about_ca_system_score_gemma":0.003106921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01864799,"about_ca_topic_score_gemma":0.02372779,"domain_scores_codex":[0.9992278,0.000133318,0.00008093983,0.0001174756,0.0003565531,0.00008410416],"domain_scores_gemma":[0.9841546,0.009881769,0.0006075334,0.0007605336,0.003941913,0.0006536987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005022115,0.00006801619,0.0003648755,0.0003355711,0.000009355174,0.00003069893,0.00002412539,0.001815168,0.0001420552,0.002479813,0.9808859,0.01379429],"study_design_scores_gemma":[0.000612411,0.00009740672,0.003333698,0.0007481584,0.00003103203,0.0001017494,0.0002153756,0.01690495,0.001351391,0.01613245,0.9603835,0.00008785816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0007775991,0.0001059328,0.01675518,0.003069082,0.0007864051,0.0006536187,0.886844,0.01187588,0.07913237],"genre_scores_gemma":[0.0244054,0.0006983605,0.05382112,0.002470041,0.0009051758,0.003050331,0.7020551,0.01803403,0.1945603],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8928131,"threshold_uncertainty_score":0.1528891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04288890292875484,"score_gpt":0.3908827522508979,"score_spread":0.3479938493221431,"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."}}