{"id":"W2745795646","doi":"10.2139/ssrn.3006813","title":"Cost-Benefit Analysis of Family Service Delivery: Disease, Prevention, and Treatment","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Business; Service delivery framework; Service (business); Medicine; Risk analysis (engineering); Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.00641654,0.001458923,0.0026683,0.00284116,0.0003773903,0.001707715,0.001296514,0.001625263,0.01125453],"category_scores_gemma":[0.01678807,0.0008053892,0.00565975,0.002587178,0.0006087553,0.001779731,0.0011581,0.001408313,0.0003766376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006295701,"about_ca_system_score_gemma":0.00355991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01549431,"about_ca_topic_score_gemma":0.01402811,"domain_scores_codex":[0.9922636,0.006007235,0.00026443,0.0002526033,0.0006278077,0.000584455],"domain_scores_gemma":[0.9919626,0.006457267,0.0005549775,0.0002148184,0.0004277261,0.0003826853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.1826723,0.004628365,0.09650694,0.005524155,0.0280011,0.001106296,0.0003632092,0.3822933,0.002734022,0.02557757,0.006153996,0.2644387],"study_design_scores_gemma":[0.02768257,0.04409237,0.258709,0.001777341,0.07790919,0.00265248,0.001544437,0.5416836,0.002623386,0.02675235,0.0141386,0.000434664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9111888,0.03175936,0.01907284,0.004916675,0.0003411385,0.00345102,0.008127391,0.0001507894,0.02099198],"genre_scores_gemma":[0.9904033,0.002877969,0.003371771,0.0002404689,0.0001022054,0.0002877981,0.0009411162,0.00001266568,0.001762575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01549431,"threshold_uncertainty_score":0.04567868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03058069838448793,"score_gpt":0.3667129883460465,"score_spread":0.3361322899615586,"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."}}