{"id":"W2959102885","doi":"10.2196/13939","title":"An Intergenerational Information and Communications Technology Learning Project to Improve Digital Skills: User Satisfaction Evaluation","year":2019,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Psychological intervention; Psychology; Medical education; Digital learning; Applied psychology; Knowledge management; Computer science; Pedagogy; Medicine","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":[0.01591761,0.0008146387,0.001015954,0.001024973,0.001333149,0.001528162,0.001350151,0.001041958,0.005375017],"category_scores_gemma":[0.0146296,0.0004525565,0.00103584,0.0007306475,0.0008798699,0.000874741,0.002839497,0.001353318,0.0007990124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312513,"about_ca_system_score_gemma":0.003122379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001365917,"about_ca_topic_score_gemma":0.001618074,"domain_scores_codex":[0.9912857,0.005566086,0.0004832672,0.0005523969,0.00133399,0.0007784037],"domain_scores_gemma":[0.9879169,0.004645833,0.0009699444,0.0008768339,0.002721761,0.002868702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01744725,0.2394837,0.1035324,0.003709098,0.0006613597,0.0006608257,0.04795171,0.002171803,0.00688264,0.0008226031,0.007031881,0.5696449],"study_design_scores_gemma":[0.01357653,0.2982924,0.5711496,0.001132898,0.001081521,0.0006638709,0.05848776,0.008958115,0.01213692,0.0009433359,0.0332976,0.0002794879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918961,0.00005962979,0.001127217,0.0001244575,0.00002214608,0.00446644,0.0002664581,0.00006097801,0.001976507],"genre_scores_gemma":[0.9660256,0.0002746549,0.01309943,0.0002505034,0.00003582259,0.01706314,0.0006693949,0.0000455538,0.002535905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01591761,"threshold_uncertainty_score":0.08418137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239965436284427,"score_gpt":0.3380168766901719,"score_spread":0.3256172223273276,"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."}}