{"id":"W1990068001","doi":"10.2316/journal.206.2011.4.206-3590","title":"SEMG-BASED NEURO-FUZZY CONTROLLER FOR A PARALLEL ANKLE EXOSKELETON WITH PROPRIOCEPTION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Proprioception; Ankle; Computer science; Rigidity (electromagnetism); Physical medicine and rehabilitation; Motion (physics); Mechanism (biology); Control theory (sociology); Engineering; Artificial intelligence; Simulation; Medicine; Control (management); Structural engineering; Anatomy; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001540473,0.00009306048,0.0001281244,0.0001415567,0.00003047212,0.0000481876,0.00009691014,0.00004685832,0.000007866185],"category_scores_gemma":[0.00003942798,0.00007124151,0.00005674008,0.00004290215,0.00003176202,0.0001500249,0.000006484237,0.00007704174,0.000001192239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003091224,"about_ca_system_score_gemma":0.0000287663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001245322,"about_ca_topic_score_gemma":0.00000200046,"domain_scores_codex":[0.999312,0.00001257857,0.0003063215,0.00006665105,0.0002159641,0.00008652586],"domain_scores_gemma":[0.9992058,0.00006387281,0.0001637376,0.00004465557,0.0004732489,0.00004873507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001729115,0.0001073739,0.0009564289,0.00005866706,0.0001286827,0.000007252197,0.0004463404,0.9756515,0.001760946,0.007624801,0.0002825533,0.01280253],"study_design_scores_gemma":[0.002344777,0.0005219359,0.00917714,0.00009947519,0.00004686925,0.00005699194,0.000056936,0.9814745,0.0005736271,0.005088289,0.0004212607,0.0001381667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05051751,0.00009853197,0.947691,0.0006894576,0.0004748261,0.0002359912,0.000006786944,0.00004245518,0.0002434839],"genre_scores_gemma":[0.8872554,0.00003584178,0.1125102,0.00007527202,0.00008217704,0.000006862356,0.000006176664,0.00001599427,0.00001202637],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8367379,"threshold_uncertainty_score":0.2905144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256020341473453,"score_gpt":0.2198654275510273,"score_spread":0.2073052241362928,"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."}}