{"id":"W7125577906","doi":"10.1109/cascon66301.2025.00021","title":"Beyond Monolithic LLMs: Modular AI for Online Harassment Detection","year":2025,"lang":"","type":"article","venue":"","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"Alliance de recherche numérique du Canada","keywords":"Modular design; Harassment; Extensibility; Architecture; Blocking (statistics); Hamming distance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007133755,0.0004550322,0.0004347427,0.0005342292,0.0007348327,0.0006645868,0.0008156699,0.0004034127,0.00006758378],"category_scores_gemma":[0.000115275,0.0004646231,0.0003555275,0.001277941,0.00008428367,0.0007235467,0.0003131043,0.0005124854,0.00009101344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004052095,"about_ca_system_score_gemma":0.00041723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002749611,"about_ca_topic_score_gemma":0.0003569858,"domain_scores_codex":[0.9965681,0.0001407482,0.000784029,0.001234144,0.0004279294,0.0008450106],"domain_scores_gemma":[0.997921,0.0001072911,0.0001794731,0.001083537,0.0004961193,0.0002125679],"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":[0.0001149726,0.0005125121,0.00003581327,0.0001897538,0.0002008527,0.000005633127,0.0001771452,0.001422404,0.0239248,0.02241253,0.001317758,0.9496858],"study_design_scores_gemma":[0.001278327,0.0007466194,0.0008960708,0.0001207923,0.000100353,0.00001088678,0.00007330924,0.7507606,0.1713611,0.03138534,0.04281341,0.0004531865],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03466297,0.000630285,0.9485178,0.006445199,0.005658093,0.001371624,0.00002489958,0.0003742337,0.002314871],"genre_scores_gemma":[0.9236631,0.000204704,0.0472712,0.004605932,0.0004594382,0.0002049834,0.00001739019,0.00003181832,0.02354137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9492326,"threshold_uncertainty_score":0.9997805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050993713129978,"score_gpt":0.2755264175209228,"score_spread":0.2650164803896231,"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."}}