{"id":"W2789321103","doi":"","title":"Robust upper limb motion classification using Gaussian mixture models","year":2005,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of New Brunswick","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Mixture model; Linear discriminant analysis; Multilayer perceptron; Perceptron; Gaussian; Artificial neural network; Autoregressive model; Root mean square; Computer science; Feature (linguistics); Feature extraction; Classifier (UML); Mathematics; Statistics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006460584,0.0001624642,0.0001237163,0.0001822438,0.0001494566,0.00007218064,0.0000914203,0.0001041539,0.00002221413],"category_scores_gemma":[0.00001122936,0.000161292,0.00006673337,0.0003236765,0.00002764686,0.000710046,0.00001350258,0.0001606651,0.000005753094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075828,"about_ca_system_score_gemma":0.000005104551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003194634,"about_ca_topic_score_gemma":0.000002413096,"domain_scores_codex":[0.9992217,0.000002182364,0.0001780812,0.0001925518,0.0001453399,0.0002601087],"domain_scores_gemma":[0.9997227,0.000006564453,0.00003761691,0.00006953041,0.0001044517,0.00005918048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006206002,0.0002217462,0.01699918,0.0007079686,0.0004126139,9.867965e-7,0.007030107,0.1091857,0.5733304,0.05335366,0.04106378,0.1976318],"study_design_scores_gemma":[0.0002585964,0.00002662933,0.03834035,0.00005768218,0.00003626614,0.00001012624,0.0005683193,0.9428353,0.01069161,0.0006649658,0.006136468,0.0003736305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9320688,0.0005642397,0.02433929,0.0007908694,0.000160793,0.0002367364,0.000002583888,0.0008030037,0.04103371],"genre_scores_gemma":[0.9944327,0.0001571227,0.004842443,0.00009135579,0.0003145089,0.0000231563,0.000004928692,0.00003540885,0.00009835058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8336496,"threshold_uncertainty_score":0.6577299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04069527735021641,"score_gpt":0.2270475093243369,"score_spread":0.1863522319741205,"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."}}