{"id":"W4255891202","doi":"10.14361/9783839429570","title":"Ageing and Technology","year":2016,"lang":"en","type":"book","venue":"Science studies","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Fogarty International Center; Eberhard Karls Universität Tübingen","keywords":"Perspective (graphical); Phenomenon; Set (abstract data type); Population ageing; Technology development; Quality (philosophy); Technological change; Human life; Population; Political science; Engineering ethics; Sociology; Engineering; Computer science; Epistemology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007061939,0.0006045109,0.0004440615,0.001475605,0.002117585,0.006350363,0.000544178,0.001831847,0.01219464],"category_scores_gemma":[0.001868809,0.0001577529,0.0003503242,0.001833611,0.00526396,0.005943852,0.002274591,0.002160817,0.004702812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002177895,"about_ca_system_score_gemma":0.002443664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002292173,"about_ca_topic_score_gemma":0.002711177,"domain_scores_codex":[0.9993545,0.0002102226,0.00004695118,0.00008705691,0.0002263792,0.00007489831],"domain_scores_gemma":[0.9994169,0.0003274899,0.00003781013,0.00006242451,0.00009073363,0.00006454751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001961153,0.00004379127,0.0004393425,0.0006848552,0.000008516084,0.0002497484,0.01755476,0.0001640164,0.0004141528,0.649658,0.1446684,0.1860948],"study_design_scores_gemma":[0.000001893947,0.0000154499,0.0003361589,0.000530611,0.00000288186,0.0001998551,0.0013587,0.00002347631,0.00005228011,0.04133314,0.9561413,0.00000426047],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002991576,0.318161,0.001486359,0.01511105,0.005985413,0.00004908175,0.00005043552,0.00005530543,0.6561098],"genre_scores_gemma":[0.06090509,0.2933733,0.001879932,0.009327692,0.005029864,0.0001392196,0.0001114353,0.00007784772,0.6291556],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9978824,"threshold_uncertainty_score":0.04079509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06618428952403832,"score_gpt":0.4458253160451315,"score_spread":0.3796410265210932,"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."}}