{"id":"W4206594622","doi":"10.2196/32443","title":"Assessing COVID-19 Health Information on Google Using the Quality Evaluation Scoring Tool (QUEST): Cross-sectional and Readability Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; National Center for Advancing Translational Sciences; University of Arkansas for Medical Sciences; University of Arkansas","keywords":"Readability; Coronavirus disease 2019 (COVID-19); Medicine; Download; Family medicine; Psychology; Computer science; Disease; World Wide Web","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0313622,0.0004687287,0.001320733,0.02927153,0.0006109302,0.002518154,0.0007413783,0.0006649215,0.001853275],"category_scores_gemma":[0.1287737,0.0003768986,0.002332257,0.01344197,0.001088894,0.003272006,0.002496546,0.0005389176,0.0003637242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425529,"about_ca_system_score_gemma":0.001350617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002867759,"about_ca_topic_score_gemma":0.003922313,"domain_scores_codex":[0.9758873,0.005917847,0.009254709,0.001568496,0.006762223,0.0006094931],"domain_scores_gemma":[0.7841904,0.1067622,0.07023506,0.004346309,0.03165323,0.002812757],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005182217,0.00012717,0.9748663,0.002119767,0.0007044445,0.000182272,0.002571278,0.0001869958,0.0005153649,0.0001541906,0.001143426,0.01691036],"study_design_scores_gemma":[0.00005537524,0.0005089585,0.9923034,0.0005434716,0.0003982005,0.000597313,0.00196432,0.0008254306,0.000555366,0.0001621638,0.002042569,0.00004345101],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833118,0.002802531,0.001522651,0.0002819026,0.00003385237,0.001291203,0.008432669,0.00006828227,0.002255117],"genre_scores_gemma":[0.9870689,0.001096725,0.003563846,0.0001409766,0.00007788365,0.001464721,0.006054622,0.0000379844,0.0004942708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9686378,"threshold_uncertainty_score":0.1658612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4986306490706657,"score_gpt":0.6991779368114075,"score_spread":0.2005472877407418,"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."}}