{"id":"W4240343763","doi":"10.2196/preprints.28701","title":"Smart Assistive Technology for Cooking for People With Cognitive Impairments Following a Traumatic Brain Injury: User Experience Study (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Université de Sherbrooke; Health and Social Services Centre University Institute of Geriatrics of Sherbrooke; Centre Hospitalier Universitaire de Sherbrooke; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre for Interdisciplinary Research in Rehabilitation","funders":"","keywords":"Usability; Context (archaeology); Session (web analytics); Cognition; Applied psychology; Web usability; Computer science; Psychology; Human–computer interaction; World Wide Web","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":[0.002104205,0.0003729919,0.0005353735,0.0006035011,0.0007788537,0.0008752309,0.0003310715,0.0006447152,0.003510354],"category_scores_gemma":[0.004918481,0.0002273523,0.0006354201,0.0004673969,0.0003793383,0.0008060791,0.0007484747,0.0004568754,0.0006737415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002158364,"about_ca_system_score_gemma":0.0003136885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007189247,"about_ca_topic_score_gemma":0.001808064,"domain_scores_codex":[0.9993413,0.0003058476,0.00007822866,0.00008280911,0.00008395448,0.0001078154],"domain_scores_gemma":[0.9969698,0.001672665,0.0002486404,0.0001547421,0.0005864723,0.0003677434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00272809,0.01216157,0.2436551,0.005682179,0.000368284,0.00706963,0.4405995,0.001001028,0.02477779,0.0005651396,0.01599509,0.2453967],"study_design_scores_gemma":[0.0003699441,0.04129154,0.5399125,0.0008748659,0.0004405769,0.007493383,0.3521507,0.002978288,0.01229983,0.0002982329,0.04153758,0.0003527123],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985234,0.0001402461,0.0004858917,0.00006025252,0.00001221681,0.0000902953,0.00009476945,0.00002076603,0.0005722409],"genre_scores_gemma":[0.9941794,0.0004871332,0.002666378,0.0002081447,0.00002428556,0.0003220609,0.0002539171,0.00002036256,0.001838329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003510354,"threshold_uncertainty_score":0.01174331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03999972994919622,"score_gpt":0.3322922046382993,"score_spread":0.2922924746891031,"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."}}