{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004308788,0.0002220368,0.0003408832,0.000183365,0.002034971,0.0001170151,0.0002375421,0.0002047291,0.0001243801],"category_scores_gemma":[0.0003251219,0.0001802484,0.00003764117,0.0009254885,0.0003234015,0.0001730609,0.0007847708,0.0001924362,0.000001814571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007435818,"about_ca_system_score_gemma":0.0003355685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002790552,"about_ca_topic_score_gemma":0.05595896,"domain_scores_codex":[0.9981126,0.00009245562,0.0002486556,0.0005742995,0.000370487,0.0006014978],"domain_scores_gemma":[0.9989351,0.0002047718,0.0002307445,0.000205782,0.0003270236,0.00009659697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001433556,0.0001693647,0.9585941,0.00006732289,0.0008059557,0.00005605208,0.02495624,0.000001773928,0.00007220863,0.001325643,0.0002806647,0.01352735],"study_design_scores_gemma":[0.01166225,0.002754833,0.6375479,0.01085846,0.003407069,0.0001269864,0.3010857,0.0002197281,0.007977434,0.00244067,0.01978565,0.002133345],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864771,0.00167889,0.006225588,0.003138504,0.00009892461,0.0009836854,0.00001268392,0.0004184932,0.0009660817],"genre_scores_gemma":[0.9864933,0.000132305,0.01234417,0.0002289138,0.00006694665,0.0002933361,0.00000937144,0.00003510488,0.000396502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210462,"threshold_uncertainty_score":0.9992642,"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."}}