{"id":"W4384562179","doi":"10.1177/17298806231183571","title":"Assistive feeding robot for upper limb impairment—Testing and validation","year":2023,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Identification (biology); Robot; Robotic arm; Software; Human–computer interaction; Degrees of freedom (physics and chemistry); Artificial intelligence; Simulation; Embedded system","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":[0.001267919,0.00065799,0.0004922342,0.0005400191,0.0002530203,0.0002201019,0.0009913944,0.0008239775,0.002266381],"category_scores_gemma":[0.002756743,0.0001932143,0.0003454816,0.0002109508,0.0004547282,0.0003517963,0.0006113429,0.0003004361,0.000733447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001540378,"about_ca_system_score_gemma":0.0004518845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008289223,"about_ca_topic_score_gemma":0.0006799041,"domain_scores_codex":[0.9992409,0.000152264,0.00007332372,0.0000815649,0.0003713991,0.00008052083],"domain_scores_gemma":[0.9986942,0.0003219504,0.00009514122,0.0001781076,0.0006288142,0.00008180852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002420443,0.003213854,0.02070099,0.003201797,0.0002200317,0.002994032,0.002195205,0.03164864,0.623705,0.001366141,0.006242654,0.3020913],"study_design_scores_gemma":[0.0007523046,0.05354203,0.09781204,0.0005261056,0.0002971081,0.006646118,0.001887167,0.2022199,0.6038237,0.0007379936,0.03150913,0.0002463781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337166,0.0003736437,0.06083039,0.0001618892,0.0001330411,0.00088886,0.0003957801,0.001311309,0.002188553],"genre_scores_gemma":[0.9634149,0.0002990541,0.03048737,0.0001099134,0.00001831841,0.0006036152,0.0005131129,0.00006030235,0.004493367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002266381,"threshold_uncertainty_score":0.00758177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1033891596972185,"score_gpt":0.4446973321484864,"score_spread":0.341308172451268,"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."}}