{"id":"W4311350785","doi":"10.1007/s11948-022-00424-y","title":"Correction: Equity in AgeTech for Ageing Well in Technology-Driven Places: The Role of Social Determinants in Designing AI-based Assistive Technologies","year":2022,"lang":"en","type":"erratum","venue":"Science and Engineering Ethics","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Equity (law); Philosophy of science; Engineering ethics; Knowledge management; Public relations; Business; Psychology; Sociology; Political science; Computer science; Engineering; Epistemology; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00532645,0.002580001,0.001552047,0.002842627,0.005097221,0.005197752,0.00349143,0.009055012,0.05692499],"category_scores_gemma":[0.09517359,0.001085335,0.001306282,0.002808909,0.003778679,0.003281916,0.002816134,0.01769571,0.0396639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006044516,"about_ca_system_score_gemma":0.01035814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03872159,"about_ca_topic_score_gemma":0.03593167,"domain_scores_codex":[0.9933903,0.001121496,0.001307539,0.0007985491,0.002934709,0.0004474515],"domain_scores_gemma":[0.9444663,0.01500275,0.002576723,0.002768449,0.03376132,0.001424437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001509858,0.000002620538,0.00005119629,0.00006318968,0.00000377959,0.0001518258,0.00008629118,0.00002944501,0.00002466413,0.001432408,0.9950041,0.003135356],"study_design_scores_gemma":[0.00002292498,0.0000094366,0.0005282308,0.000423561,0.00001719921,0.0005068634,0.0002806314,0.0002559153,0.0003017059,0.002581264,0.9950289,0.00004335478],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0002738596,0.0007937176,0.00133909,0.1319463,0.8558301,0.00003395699,0.002169744,0.000539001,0.007074108],"genre_scores_gemma":[0.03141414,0.009663468,0.01357428,0.2022316,0.2538025,0.0005444477,0.004639773,0.004321327,0.4798085],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05692499,"threshold_uncertainty_score":0.190433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03212431717840532,"score_gpt":0.3416231316527512,"score_spread":0.3094988144743459,"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."}}