{"id":"W2012790437","doi":"10.1115/smasis2011-4952","title":"Digital Resistance-Map Generation for a Magnetorheological Damper Based Platform for Rehabilitation Applications","year":2011,"lang":"en","type":"article","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Damper; Magnetorheological fluid; Process (computing); Motion (physics); Actuator; Magnetorheological damper; Controller (irrigation); Computer science; Rehabilitation; Motion controller; Engineering; Robot; Simulation; Control theory (sociology); Control engineering; Motion control; Artificial intelligence; Control (management)","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":[0.0001756412,0.000380219,0.0002406739,0.0004375185,0.0002185154,0.0003388092,0.0007225988,0.0003768112,0.004571648],"category_scores_gemma":[0.0003254095,0.0001855668,0.0002721694,0.0001566879,0.0002035139,0.0004879052,0.0004309466,0.0002572857,0.000834151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001613874,"about_ca_system_score_gemma":0.0002461671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002557707,"about_ca_topic_score_gemma":0.0003412264,"domain_scores_codex":[0.9998482,0.00001444798,0.000009045128,0.00002940852,0.00008622847,0.0000126242],"domain_scores_gemma":[0.9998689,0.00002959911,0.00002511706,0.0000302785,0.00003421283,0.00001189996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002155518,0.0001357727,0.000553036,0.0006094144,0.00003123487,0.0005865425,0.000322617,0.0489422,0.7651432,0.01197944,0.00287558,0.1686054],"study_design_scores_gemma":[0.00009251592,0.0008855905,0.002211948,0.00008393351,0.00006829429,0.001177069,0.0001228946,0.444659,0.4577395,0.005035987,0.08781499,0.0001083474],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03789333,0.0002194969,0.9517547,0.000123294,0.0001077902,0.0001945334,0.0001092225,0.002317513,0.007280088],"genre_scores_gemma":[0.4959753,0.0002630385,0.4924396,0.00008290185,0.00003330699,0.0003737403,0.0002102341,0.000216588,0.01040536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004571648,"threshold_uncertainty_score":0.01529366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04644919270276986,"score_gpt":0.2851976280623523,"score_spread":0.2387484353595825,"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."}}