{"id":"W4281896796","doi":"10.3390/mi13060842","title":"Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach","year":2022,"lang":"en","type":"article","venue":"Micromachines","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Fuzzy logic; Ambiguity; Computer science; Process (computing); Set (abstract data type); Generator (circuit theory); Artificial intelligence; Fuzzy control system; Control engineering; Engineering","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":[0.0002827462,0.0003669476,0.0003814393,0.000409978,0.000361031,0.0006143024,0.0007044013,0.0005272929,0.0028952],"category_scores_gemma":[0.0004137241,0.0001694035,0.0003980819,0.0001971491,0.0002730336,0.000403536,0.0002480704,0.0003940544,0.0005735256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004141047,"about_ca_system_score_gemma":0.0006112465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002914322,"about_ca_topic_score_gemma":0.003280011,"domain_scores_codex":[0.9998233,0.00002846885,0.00001371756,0.00004739113,0.00006934619,0.00001785895],"domain_scores_gemma":[0.9998801,0.00004241768,0.00001353102,0.000010432,0.00004498091,0.000008499691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003943109,0.0003692451,0.002135794,0.0005614827,0.0001273998,0.0005380702,0.000350324,0.3544459,0.1397348,0.02455479,0.003298452,0.4734894],"study_design_scores_gemma":[0.00004102254,0.0002240497,0.0007618446,0.00004662942,0.0000483669,0.0001754588,0.00004662582,0.9725408,0.0153305,0.005711506,0.005046427,0.00002670106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01358782,0.0002913117,0.9791718,0.0001282032,0.0000457702,0.0001373639,0.00005358923,0.0008111083,0.005772944],"genre_scores_gemma":[0.6792944,0.0004007563,0.3119241,0.0001962758,0.0000445532,0.0003057834,0.000142053,0.00006036372,0.007631829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002914322,"threshold_uncertainty_score":0.009685457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142353747878524,"score_gpt":0.2675589496751036,"score_spread":0.2533235748872512,"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."}}