{"id":"W2116193252","doi":"10.1109/iembs.2007.4353216","title":"A planar 3DOF robotic exoskeleton for rehabilitation and assessment","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Exoskeleton; Elbow; Robot; Mechanism (biology); Computer science; Engineering; Simulation; Wrist; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004988746,0.0001096371,0.0002183221,0.0001553728,0.00006627592,0.0000358551,0.00003647513,0.00008891301,0.00002922102],"category_scores_gemma":[0.0005863361,0.00009323105,0.00006380217,0.000109183,0.00009884119,0.0001297829,0.00001051007,0.0001181432,0.000003731114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008251534,"about_ca_system_score_gemma":0.0001006607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005973455,"about_ca_topic_score_gemma":0.000002804741,"domain_scores_codex":[0.9991276,0.000002968989,0.0002405591,0.000255681,0.0001644798,0.0002087592],"domain_scores_gemma":[0.9989662,0.0003600017,0.00007552848,0.0000576621,0.0004034095,0.0001372451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00078742,0.0003659878,0.6472688,0.003039002,0.00009823542,0.000003026615,0.006065961,7.221362e-7,0.09119232,0.1492401,0.006131197,0.09580719],"study_design_scores_gemma":[0.002410705,0.002509759,0.9603826,0.0004199914,0.0001021662,0.00004150012,0.007540216,0.001946736,0.00101252,0.009485674,0.01391506,0.0002331044],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587321,0.00008795385,0.02614008,0.004951335,0.0001705445,0.001050779,0.000002308032,0.00007941471,0.00878546],"genre_scores_gemma":[0.9384094,0.00002310081,0.06052597,0.0002163076,0.00009879053,0.00005778122,0.000008920757,0.00001216196,0.0006475836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3131137,"threshold_uncertainty_score":0.3801852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753966805090015,"score_gpt":0.3283660603934021,"score_spread":0.300826392342502,"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."}}