{"id":"W4200482297","doi":"10.1145/3494987","title":"SpeeChin","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Speech recognition; Session (web analytics); Convolutional neural network; Natural language processing; Syllable; Chin; Artificial intelligence; World Wide Web","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":[0.0007472902,0.001484186,0.0005759342,0.0007535822,0.0006194589,0.001628177,0.001416561,0.0009852782,0.09165823],"category_scores_gemma":[0.001991198,0.0003804095,0.0005116335,0.0004354244,0.000385743,0.002664492,0.002459011,0.0007367847,0.06618509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004309184,"about_ca_system_score_gemma":0.0006740392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001196281,"about_ca_topic_score_gemma":0.002464951,"domain_scores_codex":[0.9993926,0.0000879181,0.00004860006,0.000169928,0.000213624,0.00008733706],"domain_scores_gemma":[0.9991922,0.0001862749,0.00005020531,0.0002029353,0.0002519574,0.0001164905],"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":[0.002162576,0.0002248969,0.002462931,0.001309079,0.00007716873,0.0007017963,0.000783092,0.001207146,0.03454939,0.01370457,0.4374037,0.5054136],"study_design_scores_gemma":[0.0001167266,0.0003858085,0.002376276,0.0001373292,0.00006415292,0.001173706,0.0002691823,0.009063441,0.02998466,0.005073917,0.9512534,0.0001014637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04797128,0.005732238,0.2535122,0.002888875,0.004458013,0.001059256,0.02670143,0.2660829,0.3915939],"genre_scores_gemma":[0.225443,0.003992553,0.1519488,0.005606821,0.001077484,0.001193535,0.0746583,0.0215981,0.5144814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09165823,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334488509768427,"score_gpt":0.2456831710635254,"score_spread":0.2323382859658411,"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."}}