{"id":"W2394883578","doi":"","title":"수능동 제어 기반 주관절 재활보조로봇의 개발","year":2015,"lang":"ko","type":"article","venue":"한국재활복지공학회 학술대회 논문집","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usability; Elbow; Test (biology); Physical medicine and rehabilitation; Robot; Human–computer interaction; Computer science; Reliability (semiconductor); Simulation; Physical therapy; Engineering; Artificial intelligence; Medicine; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003970934,0.0003169037,0.0002010145,0.0001970194,0.0002756662,0.000301503,0.0004279577,0.0003574992,0.002761457],"category_scores_gemma":[0.000534074,0.00009071654,0.0002517329,0.0001165869,0.0003327226,0.0003249355,0.0002318692,0.0001563129,0.001421241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000315655,"about_ca_system_score_gemma":0.0008928317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00305554,"about_ca_topic_score_gemma":0.005579735,"domain_scores_codex":[0.9998212,0.00003761621,0.00001720341,0.00002908258,0.00007476126,0.00002015504],"domain_scores_gemma":[0.9997843,0.00003678035,0.00002188527,0.00001357476,0.0001171866,0.00002630993],"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":[0.000425902,0.0008290757,0.0209783,0.001016878,0.00005854595,0.001010646,0.0007728726,0.005080637,0.2787466,0.002145237,0.005386662,0.6835487],"study_design_scores_gemma":[0.0005419171,0.01330232,0.2096396,0.0004100428,0.0004552038,0.01805438,0.001588979,0.09987651,0.4312528,0.002380688,0.2221996,0.0002979372],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6247255,0.003191171,0.3368054,0.001294342,0.0002995513,0.001083696,0.0002046017,0.001668694,0.03072709],"genre_scores_gemma":[0.7712777,0.001619303,0.1923052,0.0005517398,0.00008577179,0.0003901653,0.0003609905,0.0000580975,0.03335098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00305554,"threshold_uncertainty_score":0.009238005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03425249185185327,"score_gpt":0.3090047458605161,"score_spread":0.2747522540086629,"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."}}