{"id":"W7062521508","doi":"","title":"Toward Smart Classrooms: Automated Detection of Speech Analytics and Disfluency with Deep Learning","year":2020,"lang":"en","type":"dissertation","venue":"QSpace (Queen's University Library)","topic":"Advanced Power Generation Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Convolutional neural network; Deep learning; Focus (optics); Set (abstract data type); Artificial neural network; Field (mathematics); Quality (philosophy); Deep neural networks; Speech corpus; Hidden Markov model","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"],"consensus_categories":[],"category_scores_codex":[0.00001191163,0.0003098478,0.0003618785,0.0004052141,0.0000915202,0.00003867959,0.0002041009,0.0003559737,0.00003340469],"category_scores_gemma":[0.00002784544,0.0003536446,0.00006014669,0.0006816608,0.00006308279,0.0007330939,0.00005642568,0.0006024563,0.000006651502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000082665,"about_ca_system_score_gemma":0.00005138621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001743798,"about_ca_topic_score_gemma":0.0001961848,"domain_scores_codex":[0.9990993,0.00003295994,0.000162302,0.0003198644,0.0001813621,0.000204181],"domain_scores_gemma":[0.9994683,0.00003735534,0.0001582146,0.0001961663,0.00005498598,0.0000849904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004844296,0.0004192565,0.1026042,0.01987822,0.00827709,0.003453738,0.03156738,0.5905219,0.03066814,0.01446536,0.02928782,0.1640126],"study_design_scores_gemma":[0.002770197,0.001748498,0.03309264,0.00101988,0.001195364,0.000006609516,0.05487319,0.08813376,0.6427351,0.0007016577,0.1697725,0.003950597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8698682,0.0005258567,0.08725829,0.003691168,0.0007260172,0.001182509,0.00006668355,0.02098514,0.01569612],"genre_scores_gemma":[0.9777973,0.001098322,0.01013735,0.000006470951,0.0000225845,0.000001259499,0.0004304641,0.00009878812,0.01040748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.612067,"threshold_uncertainty_score":0.9998916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004870140388584084,"score_gpt":0.1746545189857529,"score_spread":0.1697843785971688,"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."}}