{"id":"W4366826511","doi":"10.1002/adsr.202300003","title":"3D Printed Electromyography Sensing Systems","year":2023,"lang":"en","type":"article","venue":"Advanced Sensor Research","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"3D printing; Electromyography; Computer science; 3d printed; SIGNAL (programming language); Process (computing); Artificial intelligence; Robotics; Field (mathematics); Human–computer interaction; Engineering; Robot; Biomedical engineering; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003135378,0.0005502321,0.0004503439,0.0006141218,0.0002242566,0.0011697,0.001208347,0.001535534,0.008711492],"category_scores_gemma":[0.0007854533,0.0003674928,0.0005818937,0.0005103309,0.0003797289,0.0008580809,0.0007865581,0.0005426221,0.00433579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004470761,"about_ca_system_score_gemma":0.0002603385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000401165,"about_ca_topic_score_gemma":0.0004271196,"domain_scores_codex":[0.9992723,0.00007594438,0.00005852051,0.0001448455,0.0004205978,0.00002781595],"domain_scores_gemma":[0.9994032,0.0001661798,0.00009347827,0.0001302414,0.0001861113,0.00002076024],"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":[0.0001749149,0.00008684031,0.0007530078,0.001072125,0.00008141074,0.001025174,0.000200668,0.01840164,0.6544659,0.009527203,0.01025352,0.3039578],"study_design_scores_gemma":[0.00007085846,0.0006217535,0.003122937,0.0002337951,0.000112752,0.003817227,0.00009380724,0.1749045,0.6284111,0.005796331,0.1826177,0.0001972476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04480866,0.006869443,0.8988456,0.001089162,0.001993327,0.0002606492,0.0008856509,0.006466144,0.03878134],"genre_scores_gemma":[0.4628761,0.005598799,0.4647947,0.001405346,0.0004975932,0.0004089124,0.0008439588,0.0002584741,0.06331605],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008711492,"threshold_uncertainty_score":0.02914286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0482024893082425,"score_gpt":0.3264562215156701,"score_spread":0.2782537322074276,"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."}}