{"id":"W4401717952","doi":"10.1109/tbiom.2024.3446846","title":"A Data Perspective on Ethical Challenges in Voice Biometrics Research","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Biometrics Behavior and Identity Science","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"Mozilla Foundation","keywords":"Biometrics; Perspective (graphical); Psychology; Engineering ethics; Computer science; Engineering; Computer security; Artificial intelligence","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2594236,0.0009880645,0.001277725,0.007590793,0.008261321,0.02455548,0.004396945,0.01043621,0.005985162],"category_scores_gemma":[0.4455342,0.001056882,0.001420274,0.01471875,0.03372061,0.02939838,0.01186718,0.01226298,0.002202603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005984853,"about_ca_system_score_gemma":0.01050339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002634289,"about_ca_topic_score_gemma":0.002956667,"domain_scores_codex":[0.696391,0.2342611,0.01692457,0.01292559,0.03697265,0.002525001],"domain_scores_gemma":[0.285726,0.5657985,0.03616786,0.07142518,0.03784678,0.003035753],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003115478,0.0001679157,0.02761609,0.001000533,0.000116853,0.0004963724,0.03861196,0.001337079,0.001750952,0.8104384,0.03374721,0.08440506],"study_design_scores_gemma":[0.00007523088,0.0002153879,0.008442544,0.003728481,0.00008886863,0.001470187,0.02742283,0.003287303,0.004478647,0.6511009,0.299486,0.0002036178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05644049,0.01285541,0.3021724,0.5470115,0.003165115,0.001320946,0.008187924,0.0002918355,0.06855447],"genre_scores_gemma":[0.5566918,0.01074999,0.2825648,0.1176759,0.00633174,0.006686675,0.006207497,0.0008241942,0.01226734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7405764,"threshold_uncertainty_score":0.9132625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2563719231205265,"score_gpt":0.4530711126378877,"score_spread":0.1966991895173612,"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."}}