{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006903229,0.0002393146,0.0003152989,0.000708581,0.0002813917,0.0001276618,0.0002121575,0.0001129349,0.00002126766],"category_scores_gemma":[0.0003315808,0.0002418433,0.00006737051,0.002148611,0.000118025,0.000191343,0.00007203248,0.0004863387,0.0006779814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001127226,"about_ca_system_score_gemma":0.00001699999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000349903,"about_ca_topic_score_gemma":0.000006991679,"domain_scores_codex":[0.9971966,0.000200572,0.0003503658,0.0004030706,0.0005877301,0.001261665],"domain_scores_gemma":[0.9985542,0.0004521926,0.00002709193,0.0005126279,0.0002599388,0.0001939499],"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":[0.00002208309,0.000005611178,0.00002403098,0.0001234807,0.00003339087,0.0001137175,0.00006951973,0.346512,0.6440507,0.0003615649,0.0005883313,0.008095514],"study_design_scores_gemma":[0.001686491,0.00028693,0.001310033,0.0005949821,0.00002269712,0.0002050389,0.001644712,0.3201196,0.413866,0.002682736,0.2558745,0.001706251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778344,0.0003241389,0.003853297,0.00005896504,0.0009788257,0.000456042,0.00002478296,0.003955546,0.012514],"genre_scores_gemma":[0.9917603,0.0006215096,0.004729365,0.0000111057,0.0002898359,0.00003898561,0.00005502555,0.0001689046,0.002325041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2552862,"threshold_uncertainty_score":0.9862083,"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."}}