{"id":"W3080437961","doi":"10.1109/rbme.2020.3019769","title":"Wearable Sensor-Based Sign Language Recognition: A Comprehensive Review","year":2020,"lang":"en","type":"review","venue":"IEEE Reviews in Biomedical Engineering","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Sign language; Gesture; Wearable computer; Computer science; Gesture recognition; Human–computer interaction; Variation (astronomy); Sign (mathematics); American Sign Language; Artificial intelligence; Speech recognition; Natural language processing; Embedded system; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001486525,0.001089583,0.001804318,0.004044209,0.0002763523,0.001276777,0.001322249,0.001264968,0.004157868],"category_scores_gemma":[0.003259131,0.0004947918,0.001195098,0.003646983,0.0003912598,0.001883681,0.0007872555,0.0008934865,0.002221369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004906022,"about_ca_system_score_gemma":0.002122638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001817506,"about_ca_topic_score_gemma":0.002373213,"domain_scores_codex":[0.9993693,0.0001033567,0.000152081,0.0001089849,0.0002321397,0.00003408308],"domain_scores_gemma":[0.9979597,0.001138803,0.0002418458,0.00003942347,0.0005694464,0.0000507006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006444929,0.00006257563,0.0003266529,0.07462478,0.0001829779,0.0001309606,0.000080808,0.0002975941,0.001274841,0.001400187,0.01860854,0.9029456],"study_design_scores_gemma":[0.00002203893,0.0003366176,0.002669033,0.04312567,0.001091291,0.001847474,0.0002569597,0.000364635,0.001522258,0.001813419,0.9468721,0.00007859552],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001076325,0.9987869,0.0002712411,0.0001512561,0.0001236715,0.000009953781,0.00003095779,0.00001003179,0.0005082721],"genre_scores_gemma":[0.0007595317,0.9983026,0.0004032555,0.0001246143,0.00008717967,0.00001336587,0.00004732076,0.000002357684,0.0002597995],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004157868,"threshold_uncertainty_score":0.01390946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07036499578637223,"score_gpt":0.3228353500198016,"score_spread":0.2524703542334294,"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."}}