{"id":"W4387576250","doi":"10.3390/s23208395","title":"Development and Testing of a Soft Exoskeleton Robotic Hand Training Device","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Exoskeleton; Thumb; Actuator; Simulation; Rehabilitation; Pneumatic actuator; Reliability (semiconductor); Work (physics); Software; Accelerometer; Computer science; Engineering; Artificial intelligence; Physical therapy; Medicine; Mechanical engineering; Surgery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001516625,0.0005052962,0.0004829432,0.0005452571,0.0002247493,0.0004810108,0.001147197,0.0008339527,0.003047129],"category_scores_gemma":[0.002282056,0.0002645603,0.0004173494,0.0001975218,0.0003676968,0.0006437436,0.0006625399,0.0002305313,0.000728665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001312306,"about_ca_system_score_gemma":0.000613781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002055013,"about_ca_topic_score_gemma":0.0002152499,"domain_scores_codex":[0.9987164,0.0002037874,0.0002014109,0.0002319188,0.0005854451,0.00006113069],"domain_scores_gemma":[0.9986672,0.0003947079,0.0001716855,0.0002169841,0.0004540242,0.00009539221],"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":[0.0005217636,0.0005688634,0.006921087,0.001701498,0.00009522497,0.0006346215,0.0004523492,0.00500146,0.8306819,0.0007806064,0.0009820296,0.1516586],"study_design_scores_gemma":[0.0005109452,0.02891275,0.06352853,0.0004228216,0.0003795484,0.004798356,0.0005167004,0.05001114,0.8090878,0.0008406247,0.04080098,0.0001899443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5357327,0.000903035,0.4542427,0.0003119545,0.0003548962,0.002382903,0.0007804682,0.002044858,0.003246468],"genre_scores_gemma":[0.8047934,0.0003911683,0.1873516,0.0002029709,0.00004071211,0.0009511057,0.0005481212,0.00007291866,0.005647899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003047129,"threshold_uncertainty_score":0.01019371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07490464265215609,"score_gpt":0.3006008812786728,"score_spread":0.2256962386265168,"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."}}