{"id":"W2793305664","doi":"","title":"Automatic Decomposition of Simulated EMG Signals","year":2005,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Decomposition; Speech recognition; Computer vision; Pattern recognition (psychology)","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":[0.0000497153,0.00009360442,0.0001356325,0.000120348,0.00004163503,0.00001592582,0.00006220284,0.00004005716,0.00008005859],"category_scores_gemma":[0.00001433884,0.00009280564,0.00004680791,0.0002658793,0.00002132859,0.0001969114,0.000008993424,0.00005943828,0.0000058439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002526895,"about_ca_system_score_gemma":0.000002622998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001496146,"about_ca_topic_score_gemma":5.313061e-7,"domain_scores_codex":[0.9994883,0.000001336304,0.0001870337,0.00007933209,0.00009877163,0.0001452166],"domain_scores_gemma":[0.9997919,0.00001973084,0.00003570873,0.00003583854,0.00008587749,0.00003097186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001286439,0.0001006287,0.003086207,0.000545692,0.0002666177,3.736087e-7,0.00228837,0.006470461,0.8458751,0.001136263,0.01309975,0.1271177],"study_design_scores_gemma":[0.0006398012,0.0001183186,0.05131859,0.0001730329,0.00005279999,0.000006018106,0.000273556,0.3740432,0.5671486,0.0005008463,0.005343094,0.0003821227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910224,0.0001940244,0.0001721059,0.00009556908,0.00003094833,0.00009783289,9.793407e-7,0.000400735,0.007985382],"genre_scores_gemma":[0.9990016,0.00003305123,0.0008267295,0.00004497815,0.00005259293,0.000007058766,0.000002055258,0.00001513454,0.00001682256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3675728,"threshold_uncertainty_score":0.3784504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008246154618422319,"score_gpt":0.2365652627403723,"score_spread":0.2283191081219499,"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."}}