{"id":"W2253397145","doi":"10.5539/gjhs.v8n9p194","title":"Multiple Sclerosis and Catastrophic Health Expenditure in Iran","year":2016,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ahvaz Jundishapur University of Medical Sciences","keywords":"Equity (law); Catastrophic illness; Health care; Health insurance; Actuarial science; Environmental health; Multiple sclerosis; Population; Logistic regression; Medicine; Business; Economics; Economic growth; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003781075,0.0001339568,0.0001885071,0.001187528,0.0004027032,0.0004950959,0.0002232624,0.0002586584,0.003357205],"category_scores_gemma":[0.002026995,0.0001055415,0.0003213559,0.00158725,0.0003119561,0.0002560728,0.000436527,0.0005341386,0.0001111708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007986397,"about_ca_system_score_gemma":0.001065959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01839504,"about_ca_topic_score_gemma":0.01931934,"domain_scores_codex":[0.9996001,0.0001084871,0.00004249009,0.00003351026,0.0001045376,0.0001108152],"domain_scores_gemma":[0.9987972,0.0001677992,0.0007143729,0.00002274902,0.0001127244,0.0001851382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003380207,0.00005696931,0.9954463,0.00003341374,0.00003347259,0.0002252619,0.0002072791,0.00007208715,0.00002599896,0.0001539114,0.0005774718,0.003134106],"study_design_scores_gemma":[0.000002707301,0.00002833405,0.9981342,0.00002409093,0.00001287652,0.0004153925,0.0007300721,0.0001147277,0.00001117031,0.0001003567,0.0004224971,0.000003498823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967038,0.0006476801,0.00002309052,0.0009044198,0.000009884582,0.000007678149,0.0003427957,0.000001786285,0.00135896],"genre_scores_gemma":[0.9993067,0.0003537032,0.00002705124,0.00004506169,0.00001619306,0.00000337181,0.00014263,4.067736e-7,0.000104985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01839504,"threshold_uncertainty_score":0.03657591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068770899524021,"score_gpt":0.3824860863329994,"score_spread":0.2756089963805973,"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."}}