{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001491348,0.0001367538,0.0004129029,0.00006261094,0.00129649,0.0000175347,0.0001752188,0.0001490656,0.000649407],"category_scores_gemma":[0.0003422731,0.00007193398,0.00001363416,0.00005211533,0.0006990398,0.0007975496,0.00009665822,0.0003415651,0.000002263698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001266642,"about_ca_system_score_gemma":0.00008090409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000302402,"about_ca_topic_score_gemma":0.0001223297,"domain_scores_codex":[0.9983239,0.0002246422,0.0007970388,0.0002004758,0.0001486192,0.0003053862],"domain_scores_gemma":[0.9981616,0.0002493189,0.0009772764,0.0003249469,0.0001594277,0.0001274245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003663863,0.00002023767,0.8483835,0.0005204687,0.00002352018,0.000005087142,0.1366954,1.376874e-7,0.00001324338,0.0004563551,0.005139125,0.008376488],"study_design_scores_gemma":[0.001529719,0.0002785357,0.9165004,0.0002230522,0.00004666056,0.00002867494,0.04986177,0.0004639408,0.000002320208,0.00002042311,0.03093844,0.0001059945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846076,0.0003596691,0.002518519,0.009419002,0.0004698474,0.0004195037,0.000008609885,0.00001372978,0.002183496],"genre_scores_gemma":[0.9953621,0.0001507196,0.0003344821,0.002307938,0.0003573126,0.00006550378,0.00001117171,0.000005244059,0.001405503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08683367,"threshold_uncertainty_score":0.9971685,"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."}}