{"id":"W4308532027","doi":"10.3390/data7110154","title":"Dataset on Force Myography for Human–Robot Interactions","year":2022,"lang":"en","type":"article","venue":"Data","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Electrical impedance myography; Wearable computer; Robot; Computer science; Biosignal; Human–robot interaction; Human–computer interaction; Simulation; Artificial intelligence; Medicine; Computer vision; Embedded system","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":[0.0008663116,0.002962078,0.001617361,0.002451641,0.00086625,0.001019259,0.002227816,0.002964993,0.012192],"category_scores_gemma":[0.003099411,0.0003715953,0.001295186,0.002606011,0.0004362319,0.0006522555,0.001920547,0.001147154,0.01965464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006369939,"about_ca_system_score_gemma":0.001108784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009720175,"about_ca_topic_score_gemma":0.02185244,"domain_scores_codex":[0.9986092,0.0002013417,0.0001862213,0.0003713277,0.0004708185,0.0001611703],"domain_scores_gemma":[0.9984621,0.000304814,0.0001945906,0.0004225575,0.0004603677,0.0001555388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001000453,0.0006072373,0.01328739,0.004347803,0.0004608678,0.001129269,0.0002266031,0.004862995,0.008066016,0.001024992,0.8665119,0.09847448],"study_design_scores_gemma":[0.0005324006,0.0005796024,0.1318156,0.001049183,0.0002535036,0.002472657,0.0006559086,0.01266763,0.01040479,0.003025158,0.8363011,0.0002425841],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01224498,0.00193565,0.003999457,0.0003589957,0.0002683535,0.0004033268,0.9720272,0.003695808,0.005066396],"genre_scores_gemma":[0.01305443,0.0003669042,0.003615842,0.0001062821,0.00004572338,0.000535614,0.9802676,0.00007797506,0.001929698],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.012192,"threshold_uncertainty_score":0.04078633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06786186037731555,"score_gpt":0.3114669405129129,"score_spread":0.2436050801355973,"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."}}