{"id":"W4386838331","doi":"10.18280/ria.370420","title":"Non-Invasive Tongue-Based HCI System Using Deep Learning for Microgesture Detection","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Tongue; Deep learning; Artificial intelligence; Human–computer interaction; Medicine; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003185466,0.0005991026,0.0006993655,0.0004796585,0.0001958274,0.0005162285,0.0008088085,0.0006785764,0.003397608],"category_scores_gemma":[0.0007429839,0.0002605407,0.0004075057,0.0002305146,0.0001869397,0.00056458,0.0009301433,0.0003785022,0.00112835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002615464,"about_ca_system_score_gemma":0.0003395333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009779857,"about_ca_topic_score_gemma":0.001997025,"domain_scores_codex":[0.9997376,0.00002771533,0.00002289719,0.00006652108,0.0001148156,0.00003059501],"domain_scores_gemma":[0.999763,0.00006677931,0.00002841381,0.00002572505,0.00009035817,0.00002584794],"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":[0.0009165463,0.0002856919,0.007977302,0.000801563,0.0001254014,0.00141445,0.0003885784,0.003635457,0.3908946,0.0006896982,0.008333324,0.5845374],"study_design_scores_gemma":[0.0002787868,0.00284719,0.04911633,0.0003341354,0.0004238365,0.006667264,0.0004295583,0.6383086,0.2712901,0.002222795,0.02777814,0.0003033634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2001963,0.002599283,0.7784342,0.0005690734,0.0004167856,0.0005532026,0.0007828932,0.008825185,0.007623041],"genre_scores_gemma":[0.7852767,0.001519746,0.1956284,0.001207285,0.0001607929,0.0004969397,0.0007552647,0.0001811275,0.0147737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003397608,"threshold_uncertainty_score":0.01136613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0414229182986799,"score_gpt":0.2964167679745943,"score_spread":0.2549938496759144,"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."}}