{"id":"W4405489365","doi":"10.1109/embc53108.2024.10781656","title":"BioPoint: Enhancing Human-Computer Interaction through Single-Site, Multi-Sensor Gesture Recognition","year":2024,"lang":"en","type":"article","venue":"","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gesture; Gesture recognition; Computer science; Human–computer interaction; Artificial intelligence","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":[0.0006545207,0.0008124216,0.0004890931,0.0006030073,0.0001704772,0.0006658314,0.0007899232,0.0008600935,0.005824238],"category_scores_gemma":[0.001219963,0.0002016449,0.0002803991,0.0003498294,0.0003191616,0.0007968282,0.0008728835,0.0003425082,0.00200825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002351742,"about_ca_system_score_gemma":0.000250563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009987958,"about_ca_topic_score_gemma":0.002939332,"domain_scores_codex":[0.9994835,0.00008938299,0.0000210547,0.0001163889,0.0002559788,0.00003369406],"domain_scores_gemma":[0.9996988,0.0001242536,0.00003190886,0.00002924192,0.00008607985,0.00002977636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007798176,0.0002351994,0.002908678,0.0007777177,0.0001234591,0.0003937863,0.0003242812,0.001858588,0.3999391,0.001153391,0.012566,0.5789399],"study_design_scores_gemma":[0.0003679532,0.006816551,0.09900053,0.000422717,0.0005934996,0.009840783,0.0006549773,0.2829213,0.4895616,0.006822183,0.1024273,0.0005704441],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1060295,0.003636911,0.8668696,0.0003641351,0.0004408338,0.0004601295,0.0009003427,0.01420073,0.007097849],"genre_scores_gemma":[0.5077024,0.002214684,0.4640821,0.001085714,0.0001802266,0.0005515169,0.00126484,0.0006094046,0.0223091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005824238,"threshold_uncertainty_score":0.01948404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.036750901934474,"score_gpt":0.2631699826966366,"score_spread":0.2264190807621626,"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."}}