{"id":"W4394700037","doi":"10.2196/51675","title":"Digital Literacy Training for Low-Income Older Adults Through Undergraduate Community-Engaged Learning: Single-Group Pretest-Posttest Study","year":2024,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Training (meteorology); Medical education; Psychology; Literacy; Mathematics education; Computer science; Pedagogy; Medicine; Geography; 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":[],"consensus_categories":[],"category_scores_codex":[0.002821975,0.0006736234,0.001017171,0.0006728595,0.0009863216,0.0005569351,0.0006306674,0.0008075563,0.00311621],"category_scores_gemma":[0.00319885,0.0004501385,0.0006422361,0.0002545199,0.0003944656,0.0007304459,0.0007298413,0.00121242,0.0008278366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005570108,"about_ca_system_score_gemma":0.001297803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001555403,"about_ca_topic_score_gemma":0.00321416,"domain_scores_codex":[0.9989634,0.0002514267,0.00009940821,0.0001655819,0.0002480554,0.0002721369],"domain_scores_gemma":[0.9972947,0.0005822338,0.0002073442,0.0001890076,0.0006882858,0.001038483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"nonrandomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.01048537,0.7138271,0.1025154,0.0002838875,0.0001385626,0.0002627299,0.01058474,0.0003599111,0.01340985,0.0000912666,0.001076272,0.146965],"study_design_scores_gemma":[0.006957664,0.4337055,0.5396402,0.00008947791,0.0002037078,0.0001443145,0.005792501,0.001624406,0.008833668,0.0001248079,0.002828029,0.00005578336],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989857,0.000009041152,0.00008434119,0.00001360226,0.0000068319,0.0005518242,0.00002271961,0.000009481166,0.000316495],"genre_scores_gemma":[0.9959819,0.00004313495,0.001227028,0.00008498829,0.0000201436,0.001374599,0.0001224151,0.000003571271,0.001142099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00311621,"threshold_uncertainty_score":0.01492423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03865708173383264,"score_gpt":0.3371513583515747,"score_spread":0.298494276617742,"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."}}