{"id":"W3196552959","doi":"10.1177/14713012211051885","title":"Working towards inclusion: Creating technology for and with people living with mild cognitive impairment or dementia who are employed","year":2021,"lang":"en","type":"article","venue":"Dementia","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Toronto; University of Waterloo","funders":"Horizon 2020 Framework Programme; Joint Programming Initiative More Years, Better Lives","keywords":"Dementia; Workforce; Inclusion (mineral); Psychology; Participatory design; Citizen journalism; Cognitive impairment; Cognition; Gerontology; Psychiatry; Medicine; Social psychology; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01509196,0.0007931938,0.000575803,0.001757946,0.01211927,0.01044183,0.001577336,0.002916499,0.003420972],"category_scores_gemma":[0.02203086,0.0004087038,0.001022118,0.001169378,0.008308393,0.008807728,0.01885082,0.002653935,0.001005853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001549243,"about_ca_system_score_gemma":0.005087426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001710882,"about_ca_topic_score_gemma":0.002380438,"domain_scores_codex":[0.9831166,0.01365976,0.0005145667,0.0004724495,0.001185346,0.001051218],"domain_scores_gemma":[0.9882445,0.007180843,0.000907184,0.0009343674,0.0007257611,0.002007155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006657057,0.0003237109,0.01129178,0.0005791399,0.00002617703,0.001401272,0.8899213,0.00007206443,0.001387738,0.004759411,0.003489411,0.08668154],"study_design_scores_gemma":[0.00003656067,0.0006570288,0.008051679,0.001355365,0.00007456456,0.002273162,0.8463031,0.0002365044,0.001179212,0.009282485,0.1304632,0.00008711396],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9028133,0.003046583,0.01637056,0.01613616,0.0004829224,0.0005923987,0.00007077678,0.0002035697,0.06028374],"genre_scores_gemma":[0.9778574,0.00227398,0.01256706,0.001618821,0.0001219675,0.0004477443,0.00006407277,0.00003581855,0.005013196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01509196,"threshold_uncertainty_score":0.07981485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777271853409387,"score_gpt":0.2826205453765274,"score_spread":0.2648478268424336,"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."}}