{"id":"W4415881819","doi":"10.5753/jbcs.2025.5525","title":"Fake News Detection in Portuguese Under Large Language Model-Generated Content","year":2025,"lang":"","type":"article","venue":"Journal of the Brazilian Computer Society","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Universidade de São Paulo; Fundação de Amparo à Pesquisa do Estado de São Paulo; International Business Machines Corporation","keywords":"Fake news; Language model; Social media; Portuguese; Sample (material); Content (measure theory); Deep learning","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":[0.002013287,0.0002350393,0.000425438,0.0001285817,0.000517946,0.0002865979,0.0007500458,0.0002940191,0.00008819741],"category_scores_gemma":[0.00009119674,0.0001698738,0.0007972289,0.001154861,0.0001553391,0.0008394758,0.000210072,0.0008292542,0.000008615783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006312582,"about_ca_system_score_gemma":0.0009547041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002164078,"about_ca_topic_score_gemma":0.00151914,"domain_scores_codex":[0.997097,0.0004085704,0.001130036,0.000171149,0.0006970629,0.0004962102],"domain_scores_gemma":[0.9981448,0.0000814684,0.0008890928,0.0002975747,0.0003815477,0.0002054848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002623507,0.001276873,0.001709443,0.0002503505,0.001080244,0.00001895381,0.4728884,0.1022309,0.003388216,0.004636925,0.1739299,0.2383274],"study_design_scores_gemma":[0.004426166,0.0001439788,0.02939476,0.0007178955,0.0001299019,0.00002351722,0.06964148,0.8853099,0.001688491,0.0009128784,0.007196573,0.0004144426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7565379,0.001150525,0.2194301,0.0140115,0.005813451,0.0005001347,0.00001874557,0.00002762646,0.002510007],"genre_scores_gemma":[0.9810243,0.0006480765,0.001151859,0.01232832,0.0005293999,4.721635e-7,0.00000118779,0.00001100162,0.00430542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.783079,"threshold_uncertainty_score":0.6927254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02797824289358833,"score_gpt":0.2982061176617501,"score_spread":0.2702278747681618,"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."}}