{"id":"W4289326033","doi":"10.1145/3274386","title":"Opinion Conflicts","year":2018,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Incivility; Reputation; Baseline (sea); Computer science; Sentiment analysis; Fake news; Social media; Fraction (chemistry); Psychology; Computer security; Internet privacy; Social psychology; World Wide Web; Artificial intelligence; Political science","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":[0.002234871,0.0006323222,0.0004889059,0.0009370191,0.002356327,0.004245949,0.00112395,0.001754508,0.06159784],"category_scores_gemma":[0.01663902,0.0002458425,0.0005285804,0.0008767842,0.0009107878,0.004226599,0.002729553,0.001284958,0.01580302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212411,"about_ca_system_score_gemma":0.0006911739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001694681,"about_ca_topic_score_gemma":0.002003462,"domain_scores_codex":[0.9963334,0.0009839962,0.0002852475,0.0007589427,0.001213587,0.0004247421],"domain_scores_gemma":[0.9932526,0.002655518,0.001132583,0.000720471,0.001791574,0.0004473527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007022677,0.0001953089,0.02710588,0.000940369,0.0002078289,0.002563168,0.01211892,0.001976574,0.01014619,0.2324103,0.2460755,0.4655576],"study_design_scores_gemma":[0.00008936454,0.0001615682,0.01169376,0.0002660071,0.0001284635,0.002325999,0.008258586,0.01353875,0.004482655,0.1186265,0.8403242,0.0001042483],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1030793,0.004840074,0.08464078,0.0189467,0.003880819,0.0007471701,0.006676434,0.001242783,0.775946],"genre_scores_gemma":[0.8107247,0.001812966,0.01967282,0.008493567,0.00175614,0.0004671194,0.005265016,0.0003980344,0.1514095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06159784,"threshold_uncertainty_score":0.2060653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05491092177609213,"score_gpt":0.3229254744530044,"score_spread":0.2680145526769123,"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."}}