{"id":"W4283723687","doi":"10.1109/i2mtc48687.2022.9806595","title":"Evaluation of interpolation methods for EMG arrays","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Interpolation (computer graphics); Spline interpolation; Linear interpolation; Trilinear interpolation; Electrode; Multivariate interpolation; Spline (mechanical); Nearest-neighbor interpolation; Computer science; Mathematics; Bilinear interpolation; Materials science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Physics","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":[0.001540222,0.0001237651,0.0001488629,0.0005783626,0.0001535955,0.00002020259,0.0001714967,0.00004996896,0.0003410561],"category_scores_gemma":[0.0001111845,0.000143149,0.00005038998,0.000294801,0.00006103727,0.000150897,0.00003814036,0.0001509854,3.599505e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002888135,"about_ca_system_score_gemma":0.00006092133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008213874,"about_ca_topic_score_gemma":0.00002456417,"domain_scores_codex":[0.9985583,0.00009934889,0.0003336223,0.0001969945,0.0006789854,0.0001327818],"domain_scores_gemma":[0.9989962,0.00003043015,0.0001383926,0.0001107931,0.000701707,0.00002247821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003070265,0.00005744953,0.000813343,0.00002124157,0.0003731263,6.271154e-8,0.0004362877,0.0008254392,0.3042864,0.009384953,0.0007938747,0.6829771],"study_design_scores_gemma":[0.004516921,0.0005375073,0.006438849,0.00006262717,0.0003618954,0.00001675981,0.009407046,0.6363604,0.283682,0.03665115,0.0213888,0.000576035],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3942026,0.0007238559,0.5896022,0.002610679,0.003456861,0.001641959,0.00007491693,0.0004409739,0.007245983],"genre_scores_gemma":[0.9921713,0.0001043606,0.006700587,0.00005387826,0.00002231682,0.0008710928,0.00004451121,0.00001253612,0.0000194132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6824011,"threshold_uncertainty_score":0.5837446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110237374137625,"score_gpt":0.3555376617641631,"score_spread":0.2453002876265381,"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."}}