{"id":"W1781742586","doi":"10.1186/s12889-015-1958-0","title":"Assessment of the Chinese Resident Health Literacy Scale in a population-based sample in South China","year":2015,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"National Natural Science Foundation of China","keywords":"Cronbach's alpha; Item response theory; Health literacy; Confirmatory factor analysis; Construct validity; Differential item functioning; Measurement invariance; Classical test theory; Scale (ratio); Test theory; Biostatistics; Population; Psychometrics; Medicine; Literacy; Statistics; Psychology; Clinical psychology; Structural equation modeling; Public health; Mathematics; Environmental health; Geography; Health care; Nursing; Cartography","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":[0.002053287,0.0002984435,0.0003693653,0.001446249,0.0006678779,0.0004058981,0.000396281,0.000396975,0.001024322],"category_scores_gemma":[0.003582869,0.0001903855,0.0003827738,0.001228495,0.000503003,0.000429319,0.0006369241,0.0003834652,0.0001294773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001123722,"about_ca_system_score_gemma":0.001803583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02235942,"about_ca_topic_score_gemma":0.02704638,"domain_scores_codex":[0.9993845,0.0001384046,0.00009587622,0.00008906129,0.0002076688,0.0000843969],"domain_scores_gemma":[0.9987782,0.0001887314,0.0003224602,0.00007976588,0.0003663482,0.0002645924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002747465,0.00006697572,0.9945798,0.00002745074,0.00002958602,0.00007504438,0.0007796616,0.00004553539,0.0003727851,0.00002538071,0.0001526257,0.003817813],"study_design_scores_gemma":[0.000005610839,0.0000469633,0.9992645,0.00000378332,0.000008296118,0.00004547873,0.0003431659,0.0001543851,0.00004332333,0.00001321422,0.00006853286,0.000002803262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995168,0.00002926277,0.00006265096,0.00003516666,0.000001926345,0.00003329538,0.00008895711,0.000002036792,0.000229967],"genre_scores_gemma":[0.999426,0.0000309901,0.0001826068,0.00002828627,0.000002604512,0.00005687246,0.0001772921,6.589309e-7,0.00009474401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02235942,"threshold_uncertainty_score":0.04445857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08790669244383022,"score_gpt":0.4904071085662794,"score_spread":0.4025004161224492,"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."}}