{"id":"W4378761496","doi":"10.1007/978-3-031-34111-3_37","title":"Multi-feature Transformer for Multiclass Cyberbullying Detection in Bangla","year":2023,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Bengali; Computer science; Artificial intelligence; Social media; Word embedding; Feature (linguistics); Embedding; Machine learning; Natural language processing; Speech recognition; World Wide Web; 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":[0.0003237629,0.0005105605,0.0004151311,0.0008915866,0.0003842837,0.0006256805,0.000393688,0.0004012507,0.004751148],"category_scores_gemma":[0.0004319808,0.0001755556,0.0005176881,0.0008395051,0.0001644916,0.0005313129,0.0003700455,0.00037952,0.003114049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003102976,"about_ca_system_score_gemma":0.0003295461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004981648,"about_ca_topic_score_gemma":0.005420778,"domain_scores_codex":[0.9997411,0.00003852478,0.0000173835,0.00007051331,0.0000696032,0.00006279442],"domain_scores_gemma":[0.9997564,0.00007109204,0.00001633152,0.00003578576,0.0001005393,0.00001979378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000636436,0.0001820431,0.00695488,0.0001477597,0.00006978116,0.0004245682,0.0001560543,0.006152191,0.120007,0.001248253,0.00828551,0.8557355],"study_design_scores_gemma":[0.00005395369,0.0005966608,0.08226395,0.00007034445,0.0003198253,0.003219944,0.0008516661,0.6146253,0.2616095,0.003137239,0.03311489,0.0001367271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5390205,0.002360638,0.4229768,0.0005010387,0.0004618136,0.0001543053,0.00326819,0.005585034,0.02567169],"genre_scores_gemma":[0.8856674,0.0006592,0.0872445,0.0001219053,0.00006223519,0.00005332063,0.002730797,0.0001955243,0.02326511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004981648,"threshold_uncertainty_score":0.01589417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01207451653107711,"score_gpt":0.2542587069343211,"score_spread":0.242184190403244,"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."}}