{"id":"W2067624812","doi":"10.1007/s10198-011-0364-5","title":"Mapping utility scores from the Barthel index","year":2011,"lang":"en","type":"article","venue":"The European Journal of Health Economics","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Centre for Advancing Health Outcomes","funders":"University of Birmingham; National Institute for Health and Care Research","keywords":"Statistics; Mean squared error; Ordinary least squares; Multinomial logistic regression; Estimator; Mathematics; Logistic regression; Econometrics; Mean absolute error; Index (typography); Regression; Medicine; Computer science","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0705088,0.0002382511,0.001038152,0.0001726101,0.0005776901,0.0001100239,0.001361279,0.00004792945,0.0005426862],"category_scores_gemma":[0.00186152,0.0001868677,0.0002693704,0.0001232784,0.0002203015,0.000475617,0.0001531075,0.0005848021,0.001283081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003353467,"about_ca_system_score_gemma":0.0003950954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00129411,"about_ca_topic_score_gemma":0.0001701166,"domain_scores_codex":[0.9887737,0.003189379,0.007089294,0.0003544019,0.00007425049,0.0005189501],"domain_scores_gemma":[0.9892544,0.001488877,0.007997004,0.0009221452,0.00008385473,0.0002536935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002464968,0.0004093834,0.5635611,0.0003062368,0.000936259,0.00001664901,0.1158838,0.0003180463,0.00000128044,0.05616675,0.2217028,0.04045121],"study_design_scores_gemma":[0.001029775,0.000169886,0.7527589,0.0001468698,0.000007654143,0.00004141298,0.005053447,0.0008845596,0.000001480883,0.03510051,0.2045334,0.0002721821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.860437,0.01930317,0.01121851,0.08089717,0.003509723,0.0007979186,0.0003019248,0.00004202458,0.02349253],"genre_scores_gemma":[0.9649965,0.002920029,0.001371713,0.0291552,0.001360543,0.000004411717,0.000006199215,0.00006440849,0.0001209536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1891977,"threshold_uncertainty_score":0.9994946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5251976594514961,"score_gpt":0.3821033951129655,"score_spread":0.1430942643385306,"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."}}