{"id":"W1967390644","doi":"10.2196/jmir.8.4.e27","title":"eHEALS: The eHealth Literacy Scale","year":2006,"lang":"de","type":"article","venue":"Journal of Medical Internet Research","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":2724,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto; Toronto Public Health","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"eHealth; Health literacy; Context (archaeology); Literacy; Population; Scale (ratio); Computer science; Data science; Psychology; Health care; Medicine; Environmental health; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001208167,0.0003535844,0.0005061175,0.001059381,0.0003510282,0.0005866471,0.000708283,0.0005531415,0.008765513],"category_scores_gemma":[0.004857673,0.0002437587,0.0007996506,0.0007944184,0.0001882655,0.001231065,0.001156574,0.001328705,0.001624788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006307082,"about_ca_system_score_gemma":0.0008390465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002849369,"about_ca_topic_score_gemma":0.006769277,"domain_scores_codex":[0.998862,0.0002164033,0.0002323216,0.00007399332,0.0005061037,0.000109225],"domain_scores_gemma":[0.9983009,0.0004106576,0.0004629902,0.0000632421,0.0005270218,0.00023531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002931791,0.005452453,0.5680229,0.001555608,0.0006861344,0.0003984274,0.002123435,0.001349257,0.003567925,0.00124309,0.07712417,0.3355448],"study_design_scores_gemma":[0.0004506036,0.0008770835,0.9714299,0.0002764294,0.000123652,0.0002848168,0.0004709863,0.0008329767,0.0008825378,0.0006482442,0.02366285,0.00005990989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048109,0.001924176,0.003329233,0.002323353,0.0002358961,0.006907591,0.03202201,0.0006180488,0.04782876],"genre_scores_gemma":[0.9249187,0.001836088,0.01966904,0.001901632,0.0001262492,0.01094298,0.02153319,0.00007791707,0.01899431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008765513,"threshold_uncertainty_score":0.02932358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146206546977595,"score_gpt":0.5683213358524738,"score_spread":0.4537006811547143,"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."}}