{"id":"W2109945587","doi":"10.1109/bsn.2006.57","title":"Using Wearable Sensors to Measure Motor Abilities following Stroke","year":2006,"lang":"en","type":"article","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University","keywords":"Wearable computer; Rehabilitation; Physical medicine and rehabilitation; Stroke (engine); Computer science; Medicine; Physical therapy; Engineering; Embedded system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002720742,0.0004369712,0.000343412,0.000482469,0.0001294046,0.0003603469,0.0002745269,0.0004509717,0.001173164],"category_scores_gemma":[0.001341497,0.0001447848,0.0001594325,0.0004485918,0.0001384788,0.0003592851,0.0002376795,0.0002157909,0.0005371583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008466947,"about_ca_system_score_gemma":0.0001148214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007576708,"about_ca_topic_score_gemma":0.001256245,"domain_scores_codex":[0.9997298,0.00007577422,0.00002826555,0.00004431791,0.0001037144,0.00001813019],"domain_scores_gemma":[0.9996608,0.0001073098,0.00006140679,0.00002612699,0.000121869,0.0000224686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001730928,0.0007667816,0.1271581,0.0008406135,0.0003625472,0.0004624905,0.0005656142,0.007566788,0.2504636,0.0007132857,0.005333414,0.6040358],"study_design_scores_gemma":[0.0003304768,0.007745998,0.5328211,0.0004774139,0.0007205693,0.005119052,0.001045876,0.1560943,0.2651428,0.004063424,0.02614198,0.0002968956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.821514,0.004326307,0.1593016,0.000483376,0.0005067732,0.0003593725,0.001685897,0.001757485,0.01006519],"genre_scores_gemma":[0.9590225,0.002031773,0.03385346,0.0001948923,0.0001001285,0.0002041402,0.0007311128,0.00002285685,0.003839163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001173164,"threshold_uncertainty_score":0.003924668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836650845857698,"score_gpt":0.2837364241303466,"score_spread":0.2553699156717696,"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."}}