{"id":"W3010954129","doi":"10.22215/etd/2016-11292","title":"Quaternion-Based Human Gesture Recognition System Using Multiple Body-Worn Intertial Sensors","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Gesture; Hidden Markov model; Computer science; Gesture recognition; Support vector machine; Artificial intelligence; Set (abstract data type); Pattern recognition (psychology); Data set; Quaternion; Speech recognition; Motion (physics); Gyroscope; Computer vision; Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005141266,0.0006509378,0.0007029906,0.0006131436,0.0004040322,0.0004694407,0.0008458744,0.0008078516,0.00008867779],"category_scores_gemma":[0.00007726709,0.0005049662,0.0003572797,0.0003369103,0.00002766198,0.0004650702,0.00005981062,0.0004211249,0.0008849113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003783652,"about_ca_system_score_gemma":0.0002251799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004557868,"about_ca_topic_score_gemma":0.0005295638,"domain_scores_codex":[0.9960848,0.0004710589,0.0009957961,0.001133327,0.0007626798,0.0005523451],"domain_scores_gemma":[0.997218,0.0002512598,0.0007850462,0.0008182541,0.000700085,0.000227403],"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":[0.001522897,0.001674032,0.006113055,0.0184954,0.002274303,0.001444651,0.01302929,0.0003374906,0.3710746,0.003120178,0.008609406,0.5723047],"study_design_scores_gemma":[0.01494666,0.001152552,0.006695134,0.05464002,0.0008915414,0.0007372843,0.006112331,0.2543149,0.6370813,0.000903071,0.01087337,0.01165189],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5678199,0.0001739694,0.3957152,0.0001543789,0.0127723,0.002267009,0.0001666656,0.002510789,0.01841983],"genre_scores_gemma":[0.990721,0.000003009176,0.003179657,0.00007017468,0.00100767,0.0001097119,0.0009936441,0.00009017478,0.003824894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5606528,"threshold_uncertainty_score":0.999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066006133175471,"score_gpt":0.2779275837243353,"score_spread":0.2472675223925807,"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."}}