{"id":"W2213055291","doi":"10.2196/games.4561","title":"Engaging Elderly People in Telemedicine Through Gamification","year":2015,"lang":"en","type":"article","venue":"JMIR Serious Games","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 Information and Communication Technologies; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Conceptualization; Telemedicine; Computer science; The Internet; Population; Revenue; Psychological intervention; Knowledge management; Multimedia; World Wide Web; Health care; Medicine; Nursing; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006174754,0.0001126301,0.0001919622,0.0001281224,0.0001419448,0.00003398071,0.0003278591,0.000162349,0.00003784656],"category_scores_gemma":[0.0004641367,0.000112548,0.00002696909,0.0006704776,0.0002080208,0.0003192181,0.00004344339,0.0002584494,0.00009146735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000178313,"about_ca_system_score_gemma":0.0002021454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004688637,"about_ca_topic_score_gemma":0.03376892,"domain_scores_codex":[0.9986139,0.0001557746,0.0002258442,0.0002736585,0.0003321226,0.0003986954],"domain_scores_gemma":[0.9993734,0.00007323465,0.00008865952,0.0002802441,0.00009135999,0.00009315235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004207187,0.0002485571,0.1743305,0.0000293195,0.00001880093,0.00004071714,0.4929324,0.00001453125,0.0007052753,0.01565262,0.02267606,0.2933091],"study_design_scores_gemma":[0.001999456,0.0002635122,0.191238,0.0001038205,0.00001239445,0.00001075238,0.1493739,0.0000806699,0.0005667552,0.01340001,0.6425267,0.0004239572],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703704,0.0005270251,0.00010233,0.0139737,0.0003518869,0.0005549375,0.000001409616,0.0004778952,0.01364045],"genre_scores_gemma":[0.9977406,0.0001527163,0.0008056043,0.000219709,0.0001662364,0.0001278917,0.000005365871,0.00001513985,0.0007667537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6198507,"threshold_uncertainty_score":0.9838623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02742538226373355,"score_gpt":0.3269004621195045,"score_spread":0.299475079855771,"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."}}