{"id":"W4405360458","doi":"10.1109/tmech.2024.3509854","title":"Self-Unlocking Active Clutch for Quasi-Passive Wearable Robots","year":2024,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Foundation of Korea; Ministry of Health, British Columbia; Korea Health Industry Development Institute","keywords":"Clutch; Robot; Wearable computer; Computer science; Human–computer interaction; Engineering; Artificial intelligence; Embedded system; Automotive engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000153099,0.0003361952,0.0002845544,0.0002305425,0.0002465509,0.0001465438,0.0002352321,0.0002245713,0.000196109],"category_scores_gemma":[0.000004217727,0.0003405634,0.0002866845,0.0003498764,0.00002152284,0.0003153744,0.000002193668,0.000627614,0.0002887559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004458545,"about_ca_system_score_gemma":0.0001042081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001782358,"about_ca_topic_score_gemma":0.00005400496,"domain_scores_codex":[0.9983653,0.00002757541,0.0003188917,0.0004465031,0.0002591984,0.00058248],"domain_scores_gemma":[0.999235,0.0001786918,0.00002553176,0.0003592211,0.00006953888,0.0001319757],"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":[0.00002612326,0.000106505,1.300846e-7,0.0003282471,0.0003431001,0.000009023023,0.0008303387,0.8685011,0.002105987,0.004563524,0.0003605801,0.1228254],"study_design_scores_gemma":[0.0002204491,0.000215767,6.259452e-7,0.0001811663,0.0001406947,0.0000151986,0.0002411909,0.8601261,0.1123755,0.002197185,0.02384624,0.0004398309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002116416,0.001095854,0.990959,0.000230854,0.002859782,0.0006049572,0.00009805066,0.001262622,0.0007724353],"genre_scores_gemma":[0.9762686,0.001646507,0.02026874,0.00005266189,0.000209345,0.0003242262,0.00001001512,0.0001640811,0.001055773],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9741523,"threshold_uncertainty_score":0.9999046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388312231919523,"score_gpt":0.2456385023207691,"score_spread":0.2317553800015738,"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."}}