{"id":"W2504851880","doi":"10.1109/jbhi.2016.2593692","title":"A Microsoft Kinect-Based Point-of-Care Gait Assessment Framework for Multiple Sclerosis Patients","year":2016,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Neurological Institute and Hospital; McGill University","funders":"Biomedical Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Gait; Intraclass correlation; Gait analysis; Physical medicine and rehabilitation; Physical therapy; Medicine; Computer science; Psychometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001030605,0.000162511,0.0007094843,0.0003002016,0.0001425689,0.00001664756,0.000136496,0.0001393737,0.00002238244],"category_scores_gemma":[0.00134803,0.00008917644,0.0001806343,0.00017485,0.0003050099,0.0001558184,0.00004493054,0.0002937178,0.000002084774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375358,"about_ca_system_score_gemma":0.0007156371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009819822,"about_ca_topic_score_gemma":0.000003593586,"domain_scores_codex":[0.996884,0.00003959871,0.001667253,0.00008164661,0.0009007001,0.0004268144],"domain_scores_gemma":[0.9962803,0.0009379479,0.001041742,0.0001599523,0.0009124916,0.0006676173],"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":[0.001998436,0.001603951,0.1706941,0.01471868,0.0004263283,0.000003338593,0.004454348,0.000003143359,0.002830233,0.0001184984,0.03456942,0.7685795],"study_design_scores_gemma":[0.04994525,0.02821846,0.8366843,0.02718939,0.0002072973,0.0000292324,0.003237418,0.002864535,0.005407787,0.0004904459,0.04519797,0.0005278474],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5693948,0.0008365627,0.398082,0.02846307,0.0009512322,0.001700429,0.0005051797,0.00002614094,0.00004050908],"genre_scores_gemma":[0.8252696,0.001640855,0.1709829,0.001806036,0.0002541165,0.00001675549,0.00001127708,0.00001417943,0.000004287941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7680517,"threshold_uncertainty_score":0.3636509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08655060522703373,"score_gpt":0.3819869183073784,"score_spread":0.2954363130803446,"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."}}