{"id":"W2948407181","doi":"10.1177/1352458519852722","title":"Developing a crosswalk between the RAND-12 and the health utilities index for multiple sclerosis","year":2019,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Institute of Neurological Disorders and Stroke; Biogen","keywords":"Schema crosswalk; Intraclass correlation; Statistics; Bland–Altman plot; Concordance; Psychology; Population; Pearson product-moment correlation coefficient; Index (typography); Gerontology; Medicine; Mathematics; Limits of agreement; Psychometrics; Geography; Computer science; Environmental health; Nuclear medicine; Internal medicine","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.005772513,0.0005835262,0.001442751,0.0002859884,0.003002533,0.0006704647,0.0006835941,0.0001984914,0.00008409116],"category_scores_gemma":[0.003818314,0.0003166002,0.0006165711,0.0004243224,0.001274807,0.0003911412,0.0005107047,0.001325034,0.00003413889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004863708,"about_ca_system_score_gemma":0.0006172606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006759939,"about_ca_topic_score_gemma":0.0004308111,"domain_scores_codex":[0.9944428,0.0006884639,0.001339354,0.0006851302,0.001324953,0.001519362],"domain_scores_gemma":[0.9911522,0.006235908,0.0006344133,0.0007897208,0.0006538937,0.0005339122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004373236,0.0001072073,0.904357,0.0004323469,0.0009357061,0.000001190169,0.005695226,0.00003930335,0.001923915,0.0001351022,0.00453137,0.07746846],"study_design_scores_gemma":[0.03693376,0.0004132458,0.9408008,0.001255026,0.0001102395,0.00003931575,0.003682591,0.005412345,0.0005593083,0.0001989282,0.01021852,0.0003759483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460102,0.00460894,0.006266885,0.03674323,0.0006469745,0.005266306,0.0001788217,0.0001162617,0.0001623593],"genre_scores_gemma":[0.9864467,0.006114906,0.003248145,0.002274094,0.0009966157,0.0003917359,0.00002256158,0.0001020035,0.0004032043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07709251,"threshold_uncertainty_score":0.9999286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1989147768467572,"score_gpt":0.3414105658524792,"score_spread":0.142495789005722,"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."}}