{"id":"W4401070260","doi":"10.1109/access.2024.3435497","title":"Fake News Detection Using Deep Learning: A Systematic Literature Review","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Fake news; Social media; Data science; Focus (optics); Process (computing); Deep learning; Artificial intelligence; Polling; Class (philosophy); Witness; Transfer of learning; Internet privacy; World Wide Web","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":[0.005824616,0.001409236,0.00295311,0.009767287,0.0004662015,0.001956221,0.001824293,0.001529077,0.004498516],"category_scores_gemma":[0.03714013,0.0008065212,0.003380318,0.006724285,0.0007958785,0.002937331,0.001421938,0.001334144,0.0007992074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440214,"about_ca_system_score_gemma":0.007314627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004920558,"about_ca_topic_score_gemma":0.01353923,"domain_scores_codex":[0.9969282,0.001018832,0.0007775394,0.000386637,0.0007720339,0.0001168262],"domain_scores_gemma":[0.9671437,0.02766599,0.002042488,0.000494742,0.002427232,0.0002258235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002749999,0.0001363067,0.004595096,0.3286633,0.003284199,0.0001744037,0.0002910342,0.001106461,0.0003970522,0.001686111,0.010407,0.6489841],"study_design_scores_gemma":[0.0001955791,0.0007519188,0.01599412,0.729745,0.02648964,0.00137893,0.0009171536,0.003366295,0.00165682,0.005970888,0.2133453,0.0001883618],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00124277,0.9958876,0.001055272,0.0006304793,0.00009901513,0.00008595761,0.0003511295,0.00002512349,0.0006226686],"genre_scores_gemma":[0.01295474,0.983223,0.002285422,0.0006460071,0.0001255259,0.0001678037,0.0003854941,0.00001369988,0.000198272],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009767287,"threshold_uncertainty_score":0.03080386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05638627664275919,"score_gpt":0.3973145447769169,"score_spread":0.3409282681341577,"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."}}