{"id":"W2060075501","doi":"10.1109/isspa.2012.6310660","title":"Design of a neuromuscular disorders diagnostic system using human movement analysis","year":2012,"lang":"en","type":"article","venue":"","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Kinematics; Physical medicine and rehabilitation; Computer science; Movement disorders; Receiver operating characteristic; Stroke (engine); Diabetes mellitus; Risk analysis (engineering); Medicine; Simulation; Engineering; Machine learning; Mechanical engineering; Pathology","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":[0.002206283,0.0008783395,0.001304979,0.001640133,0.0006091052,0.001072376,0.001354859,0.001170391,0.003637919],"category_scores_gemma":[0.003009057,0.0005518518,0.0006181364,0.00052055,0.0005298796,0.0007629152,0.000863461,0.0004795769,0.002112941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005255728,"about_ca_system_score_gemma":0.001087971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337261,"about_ca_topic_score_gemma":0.001014351,"domain_scores_codex":[0.9983694,0.0003960239,0.000160542,0.0005304314,0.0004521106,0.00009150086],"domain_scores_gemma":[0.998341,0.0005762779,0.0001647634,0.0001219436,0.0006962722,0.00009981466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00175869,0.0004564218,0.01453887,0.001205882,0.0004306057,0.0007033397,0.0004985196,0.04685998,0.1941304,0.006320774,0.006745159,0.7263514],"study_design_scores_gemma":[0.0005918432,0.002673769,0.0198117,0.000226244,0.0006433087,0.002067633,0.0002096096,0.8423509,0.09850036,0.005767828,0.02691364,0.0002432119],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007379226,0.0001261046,0.9883999,0.0001021534,0.00004803441,0.0004242225,0.00008384376,0.00260466,0.0008317942],"genre_scores_gemma":[0.2055939,0.0002558413,0.789139,0.0002684727,0.000140503,0.001622856,0.0003679823,0.0001639987,0.002447414],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003637919,"threshold_uncertainty_score":0.01217002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788873615701901,"score_gpt":0.223067556468759,"score_spread":0.20517882031174,"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."}}