{"id":"W4402811968","doi":"10.1109/csr61664.2024.10679393","title":"Can Deep Learning Detect Fake News Better when Adding Context Features?","year":2024,"lang":"en","type":"article","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Context (archaeology); Fake news; Deep learning; Artificial intelligence; Internet privacy; History","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":[0.001034915,0.001343085,0.0007291193,0.001367481,0.0004024336,0.001176574,0.0006197672,0.001209958,0.002300552],"category_scores_gemma":[0.005355368,0.000279067,0.0006022932,0.0007999166,0.0003265394,0.003197353,0.0005349633,0.001644987,0.001466385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005684567,"about_ca_system_score_gemma":0.0004915525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003761179,"about_ca_topic_score_gemma":0.005981603,"domain_scores_codex":[0.9995961,0.0001060776,0.00002738185,0.0001059738,0.00006562033,0.00009880481],"domain_scores_gemma":[0.9984747,0.0007563793,0.0001922245,0.0001992738,0.0002935186,0.00008389415],"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":[0.0008428086,0.0008058961,0.04771101,0.0003977408,0.0003030236,0.0002895726,0.0002560419,0.03964408,0.01663587,0.002054765,0.0221695,0.8688896],"study_design_scores_gemma":[0.00006061017,0.0003236693,0.01515807,0.0001714877,0.00017569,0.0002378962,0.0002936054,0.9524034,0.01666993,0.00667725,0.007783281,0.0000451212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7721237,0.01327384,0.1794407,0.01027924,0.001378673,0.0001351469,0.002926227,0.004520502,0.01592199],"genre_scores_gemma":[0.9539029,0.001342172,0.03782426,0.000584835,0.0003679305,0.00003520697,0.002187513,0.00006553115,0.003689516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003761179,"threshold_uncertainty_score":0.007696152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209997171131317,"score_gpt":0.2967048040720985,"score_spread":0.2746048323607854,"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."}}