{"id":"W2767342743","doi":"10.1177/2333721417737681","title":"If You Build It, Who Will Come? A Description of User Characteristics and Experiences With the McMaster Optimal Aging Portal","year":2017,"lang":"en","type":"article","venue":"Gerontology and Geriatric Medicine","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"eHealth; Patient portal; Demographics; Health literacy; Internet portal; The Internet; Medicine; Plan (archaeology); User satisfaction; Literacy; Medical education; Psychology; Gerontology; Computer science; World Wide Web; Health care; Demography; Human–computer interaction","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":[0.001304507,0.0001643916,0.0002421525,0.0009241741,0.001425843,0.001175893,0.0003059168,0.0004308673,0.007843767],"category_scores_gemma":[0.005772702,0.0001736622,0.0003508473,0.001095061,0.000395054,0.001584175,0.001147207,0.0005691785,0.001273002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008938612,"about_ca_system_score_gemma":0.001333661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01870179,"about_ca_topic_score_gemma":0.04309674,"domain_scores_codex":[0.999124,0.0003499311,0.0001063588,0.00004163578,0.0001881084,0.0001900218],"domain_scores_gemma":[0.9964429,0.0015407,0.0005177023,0.0001164122,0.0005005521,0.0008817614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006295058,0.000806909,0.6082688,0.000952963,0.00006298526,0.002406102,0.09960143,0.0002971375,0.002182119,0.001108147,0.04240601,0.2412779],"study_design_scores_gemma":[0.00006066323,0.0009929711,0.6772658,0.0006185875,0.00007045927,0.004417729,0.1847506,0.001010518,0.00101104,0.0005483166,0.1290451,0.000208236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786298,0.0005833043,0.00103007,0.002058078,0.00003377799,0.0002683977,0.001902829,0.0001704527,0.01532333],"genre_scores_gemma":[0.9862975,0.0008910118,0.002973287,0.0008435881,0.00002246393,0.0003266285,0.0007356238,0.00003862366,0.007871239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01870179,"threshold_uncertainty_score":0.03718585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05242836581734134,"score_gpt":0.3930783353210406,"score_spread":0.3406499695036992,"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."}}