{"id":"W4393021548","doi":"10.21203/rs.3.rs-4119117/v1","title":"PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; Vector Institute","funders":"","keywords":"Fake news; Computer science; Data science; Internet privacy","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":[0.004699886,0.00220959,0.002444867,0.004631751,0.001313892,0.002884226,0.003205585,0.003171158,0.004318871],"category_scores_gemma":[0.01468244,0.0009354905,0.001443271,0.002723871,0.001440884,0.004281169,0.004591642,0.003163377,0.003580362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007517748,"about_ca_system_score_gemma":0.002406038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00764569,"about_ca_topic_score_gemma":0.01113096,"domain_scores_codex":[0.9963145,0.0008645573,0.0001982284,0.0008833921,0.001429586,0.000309716],"domain_scores_gemma":[0.9902622,0.003202438,0.0005147558,0.003155641,0.002511874,0.0003530681],"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":[0.0009071421,0.0005584449,0.004592528,0.000445365,0.0002462654,0.0003475796,0.0002347625,0.03108941,0.0284713,0.005791448,0.03097512,0.8963407],"study_design_scores_gemma":[0.0000404093,0.0001294539,0.001699337,0.0000467473,0.00009000652,0.0002885028,0.00008763113,0.9604209,0.01961637,0.007063753,0.0104623,0.00005454503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02694275,0.001215672,0.946824,0.0009190581,0.0008077229,0.0005622571,0.002215513,0.01486981,0.005643145],"genre_scores_gemma":[0.1640446,0.0006051057,0.8202929,0.0005495567,0.0007090555,0.0004023437,0.004764404,0.0008309632,0.007801072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00764569,"threshold_uncertainty_score":0.02485567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4648028201835392,"score_gpt":0.5503472354561901,"score_spread":0.08554441527265089,"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."}}