{"id":"W4285333132","doi":"10.2196/34821","title":"Development of an Assistive Technology for Cognition to Support Meal Preparation in Severe Traumatic Brain Injury: User-Centered Design Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Traumatic Brain Injury Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Université de Sherbrooke; Centre for Interdisciplinary Research in Rehabilitation; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Cognition; Assistive technology; Traumatic brain injury; Meal preparation; Meal; Assistive device; Psychology; Physical medicine and rehabilitation; Medicine; Human–computer interaction; Computer science; Neuroscience; Internal medicine; Psychiatry; Food science; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001087029,0.0001939686,0.000448306,0.001047793,0.0002369207,0.00001910694,0.0002357853,0.00008480989,0.0004052651],"category_scores_gemma":[0.000186721,0.0001939889,0.00004948742,0.0006319857,0.00004613879,0.0001240791,0.0001192292,0.0002718199,0.000006107128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005278282,"about_ca_system_score_gemma":0.0003420023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001260922,"about_ca_topic_score_gemma":0.0002731638,"domain_scores_codex":[0.9976077,0.000260994,0.0007108828,0.0004218674,0.0006540624,0.0003445006],"domain_scores_gemma":[0.9990566,0.0001577036,0.0001776039,0.0003323101,0.0001484293,0.0001273851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.02125072,0.03839859,0.3313408,0.001653348,0.001497939,0.0001007624,0.3361989,0.0001780144,0.1725866,0.0005648936,0.01287671,0.08335267],"study_design_scores_gemma":[0.009209766,0.03329643,0.8667557,0.0001388044,0.00008752517,0.00001688406,0.06727893,0.0001616546,0.02144854,0.0002760895,0.000849148,0.0004805784],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906532,8.398958e-7,0.0008278691,0.0001359895,0.00004407273,0.008075858,0.00008310676,0.00008800359,0.00009105856],"genre_scores_gemma":[0.9908249,2.804559e-8,0.004961507,0.00005405771,0.00001212159,0.003546096,0.0003413816,0.00003676448,0.0002230862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5354149,"threshold_uncertainty_score":0.791064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2047488600229966,"score_gpt":0.4460919757319893,"score_spread":0.2413431157089928,"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."}}