{"id":"W4406790439","doi":"10.1371/journal.pone.0317001","title":"Gender biases and hate speech: Promoters and targets in the Argentinean political context","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Politics; Popularity; Context (archaeology); Social media; Political science; Sociology; Law; Biology","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":[0.0002255998,0.00007799474,0.0001059717,0.00008963157,0.00007423895,0.0001387081,0.0001702994,0.00003456299,0.000004739019],"category_scores_gemma":[0.0001096154,0.00005857445,0.00001378029,0.00018539,0.00005438305,0.0001268524,0.00009258994,0.0001105876,0.000008770955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001172355,"about_ca_system_score_gemma":0.00001893898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006456363,"about_ca_topic_score_gemma":0.00003077458,"domain_scores_codex":[0.9992094,0.00007137327,0.0001127311,0.0002248508,0.0001460128,0.0002356426],"domain_scores_gemma":[0.9996245,0.0000882497,0.00001813394,0.0001914827,0.00002449692,0.00005314093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001325479,0.005164379,0.07614548,0.0009668716,0.0007067462,0.0005339473,0.01136129,0.000003102398,0.08906434,0.6300765,0.001826148,0.1840187],"study_design_scores_gemma":[0.003792781,0.0006906098,0.1751235,0.001088214,0.0002106615,0.000141394,0.001824087,0.05810847,0.6781702,0.07692572,0.002825554,0.001098776],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901581,0.0003717066,0.00253127,0.004563035,0.00004828878,0.000249741,0.000001739138,0.00005370622,0.002022401],"genre_scores_gemma":[0.9953322,0.00002935911,0.003292996,0.001123548,0.00002269883,0.000009116522,9.832215e-7,0.000003015013,0.0001860177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5891058,"threshold_uncertainty_score":0.2388597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05960972641092253,"score_gpt":0.2473307400263937,"score_spread":0.1877210136154712,"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."}}