{"id":"W2060424375","doi":"10.1097/ncn.0b013e3181cd8184","title":"The Digital Divide and Urban Older Adults","year":2010,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Digital divide; The Internet; Logistic regression; Gerontology; Population; Psychology; Independent living; Demography; Medicine; Geography; Sociology; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003935353,0.00009860999,0.0001750001,0.001163092,0.0006676962,0.0007046736,0.0001632315,0.0002965946,0.002944692],"category_scores_gemma":[0.002413368,0.00009943536,0.0001602594,0.0009672435,0.0003705626,0.0009096494,0.001077727,0.0003523749,0.0002208595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002683388,"about_ca_system_score_gemma":0.000297603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009761317,"about_ca_topic_score_gemma":0.02057483,"domain_scores_codex":[0.9997,0.00008537228,0.00003486625,0.00002735191,0.00007630196,0.00007613326],"domain_scores_gemma":[0.9986953,0.0002141433,0.0005793351,0.00004032542,0.0001440583,0.0003268895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003443909,0.0001185441,0.9882208,0.00001982232,0.00001315263,0.0001022047,0.002704261,0.00001837918,0.00006601785,0.000194751,0.0003779495,0.008129839],"study_design_scores_gemma":[0.00000399994,0.00005790323,0.9933621,0.00002369749,0.000007468183,0.0001299973,0.005150521,0.00005938953,0.00002122972,0.00008373485,0.001097471,0.000002517318],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980351,0.0002307679,0.00001554883,0.0002617922,0.000003485468,0.000004861253,0.00007111578,8.903726e-7,0.001376504],"genre_scores_gemma":[0.9993093,0.0002249314,0.00001690561,0.00007952756,0.000009307973,0.000005585048,0.00007715452,5.473073e-7,0.0002767553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009761317,"threshold_uncertainty_score":0.019409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005312693268397092,"score_gpt":0.2464950264501198,"score_spread":0.2411823331817227,"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."}}