{"id":"W4414263684","doi":"10.1080/17483107.2025.2557443","title":"Can we configure COOK, a cognitive Orthosis for meal preparation, with efficiency and effectiveness?","year":2025,"lang":"en","type":"article","venue":"Disability and Rehabilitation Assistive Technology","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université 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":"Cognition; Assistive technology; Interface (matter); Rehabilitation; Meal preparation; Orthotics","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":[0.007395621,0.0006389746,0.0003317375,0.0008077645,0.0005903184,0.002525897,0.001216548,0.001277435,0.002922167],"category_scores_gemma":[0.03428421,0.0003538094,0.0004628671,0.000418092,0.001252307,0.00360687,0.0007759325,0.000521637,0.0008097246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006254626,"about_ca_system_score_gemma":0.001461536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169035,"about_ca_topic_score_gemma":0.002107582,"domain_scores_codex":[0.9961069,0.002252664,0.000320992,0.0002522034,0.0008744077,0.0001928054],"domain_scores_gemma":[0.9936196,0.004378748,0.0006697155,0.000439396,0.0006623236,0.0002301061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009076842,0.001456409,0.02049499,0.00376035,0.00009894196,0.0002103405,0.005582113,0.001151357,0.005961964,0.001661043,0.004460176,0.9542547],"study_design_scores_gemma":[0.003081616,0.03154523,0.3234842,0.01988824,0.003246247,0.01471718,0.1278234,0.05445301,0.1131008,0.03382258,0.2735052,0.001332335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.822525,0.01628756,0.1167472,0.0109132,0.0006449486,0.00195737,0.000239865,0.001895135,0.02878968],"genre_scores_gemma":[0.849219,0.005203438,0.1410274,0.001301908,0.0001154849,0.0006645484,0.0001120249,0.0001396602,0.002216545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007395621,"threshold_uncertainty_score":0.03911227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02068786699413691,"score_gpt":0.403889671796413,"score_spread":0.3832018048022761,"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."}}