{"id":"W4391020680","doi":"10.1109/mts.2023.3340235","title":"Technological Solutions to Online Toxicity: Potential and Pitfalls","year":2023,"lang":"en","type":"article","venue":"IEEE Technology and Society Magazine","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Misinformation; Disinformation; Context (archaeology); Social media; Computer science; Process (computing); Internet privacy; Data science; Risk analysis (engineering); Computer security; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002805138,0.0001441439,0.0001769199,0.0002815187,0.0003969998,0.00005670938,0.0003543784,0.000410712,0.000003912919],"category_scores_gemma":[0.00005656653,0.0001337555,0.00005599588,0.001859926,0.0004270129,0.0001312082,0.0004879003,0.00035609,0.0001344318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002030723,"about_ca_system_score_gemma":0.00002013034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000194935,"about_ca_topic_score_gemma":0.000006601626,"domain_scores_codex":[0.9987997,0.00001790806,0.0001575067,0.0004629359,0.0001264212,0.0004354594],"domain_scores_gemma":[0.9994608,0.00002729267,0.00003344363,0.000337945,0.00004920805,0.00009134853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001218075,0.0002317226,0.0004257073,0.00003896188,0.0001140854,0.0001434388,0.0004688865,0.0001107079,0.4708462,0.1493795,0.02866394,0.3495647],"study_design_scores_gemma":[0.005425787,0.004162057,0.05004157,0.0002516254,0.000186394,0.002807747,0.003036958,0.2417111,0.1106804,0.3980975,0.17971,0.003888834],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7440355,0.0001426705,0.228949,0.02357615,0.0002195896,0.0001872251,0.000009951777,0.002782495,0.00009735556],"genre_scores_gemma":[0.9689636,0.0005348722,0.02890094,0.0006490639,0.00005153705,0.00002909888,0.00000389071,0.000009474531,0.0008575586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3601658,"threshold_uncertainty_score":0.5454392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433257319415143,"score_gpt":0.241260016478174,"score_spread":0.2269274432840226,"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."}}