{"id":"W2948009580","doi":"10.1016/j.humov.2019.05.006","title":"Classification of gait muscle activation patterns according to knee injury history using a support vector machine approach","year":2019,"lang":"en","type":"article","venue":"Human Movement Science","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Children's Hospital; Alberta Bone and Joint Health Institute; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Killam Trusts","keywords":"Hamstring; Physical medicine and rehabilitation; Gait; Treadmill; Medicine; Knee Joint; Electromyography; Osteoarthritis; Physical therapy; Rehabilitation; Surgery; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006910352,0.0004831704,0.0005975079,0.002259413,0.0002076658,0.0005012737,0.000340176,0.0004810596,0.001160522],"category_scores_gemma":[0.001553078,0.0001224027,0.0005473707,0.0008649737,0.0001864256,0.0003058448,0.0002677586,0.0003086134,0.0004351954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001320966,"about_ca_system_score_gemma":0.0002909143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002061697,"about_ca_topic_score_gemma":0.00156921,"domain_scores_codex":[0.9997136,0.00004134052,0.00005459515,0.00007782606,0.00006416399,0.00004846369],"domain_scores_gemma":[0.9992873,0.0002635997,0.00008791572,0.00004969697,0.0002437182,0.00006781223],"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":[0.001813394,0.000681604,0.1462917,0.0002190564,0.0002623565,0.0003835986,0.0002031362,0.01091752,0.04378731,0.0002765446,0.001450332,0.7937135],"study_design_scores_gemma":[0.0001115756,0.002210333,0.3380843,0.0001098077,0.0003717219,0.001248292,0.0006889624,0.6382672,0.01554169,0.001610134,0.001672745,0.00008328915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8366287,0.000713137,0.1595292,0.0001565486,0.0001350507,0.0002121604,0.0008250388,0.0007135228,0.001086605],"genre_scores_gemma":[0.9683678,0.0001523373,0.0298154,0.00002518969,0.00003715562,0.00007520976,0.000572395,0.00001441894,0.0009401579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002259413,"threshold_uncertainty_score":0.004099429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03291285238029737,"score_gpt":0.2549542391713306,"score_spread":0.2220413867910332,"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."}}