{"id":"W1535141691","doi":"10.15353/joci.v8i1.3051","title":"Overview: Technology and Aging Issue","year":2012,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Engineering ethics; Computer science; Data science; Engineering","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":[0.004376116,0.0000639029,0.0001474552,0.0002443238,0.0008798469,0.00002469489,0.0008044454,0.0001125673,0.0000199179],"category_scores_gemma":[0.0005863573,0.0000435221,0.00002445616,0.0003960614,0.0006220086,0.0006992058,0.0002435384,0.001019822,0.00001922673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004359465,"about_ca_system_score_gemma":0.00004981213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001193191,"about_ca_topic_score_gemma":0.0001103116,"domain_scores_codex":[0.9988014,0.0003901444,0.0003614442,0.000003322808,0.0002100777,0.0002336252],"domain_scores_gemma":[0.9986913,0.00041456,0.0004111144,0.0002755207,0.0001402831,0.0000672622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000006563747,0.00006183818,0.008556368,0.00003715623,0.00004521689,1.325538e-7,0.9122161,0.000003255429,0.00002597711,0.01978913,0.004776749,0.05448155],"study_design_scores_gemma":[0.0002439082,0.00006100072,0.003395861,0.00006635947,0.0000454522,0.0001358986,0.6557771,0.000006018725,0.0002357619,0.00709893,0.3328592,0.00007446472],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803111,0.001869253,0.0003224683,0.01103949,0.0001705637,0.00006864937,6.912785e-7,0.00004608476,0.00617168],"genre_scores_gemma":[0.9965178,0.001980015,0.0007279118,0.0006242172,0.00007393243,3.550028e-7,1.309646e-7,0.000003639221,0.00007202937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3280825,"threshold_uncertainty_score":0.676716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03529987788308572,"score_gpt":0.3287887701515761,"score_spread":0.2934888922684904,"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."}}