{"id":"W2977496429","doi":"10.48550/arxiv.1910.02223","title":"A Machine Learning Analysis of the Features in Deceptive and Credible News","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Artificial intelligence; Machine 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003086415,0.0007124714,0.0005689678,0.003285137,0.0008899431,0.002058291,0.0006003538,0.001229682,0.001393917],"category_scores_gemma":[0.0250529,0.0001835765,0.0006986657,0.001803559,0.0006273776,0.001661441,0.0006110382,0.001896129,0.001266218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052334,"about_ca_system_score_gemma":0.0005270992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004811842,"about_ca_topic_score_gemma":0.003075392,"domain_scores_codex":[0.9978365,0.0006207533,0.0002160964,0.0003625746,0.0007122206,0.0002518695],"domain_scores_gemma":[0.9735406,0.01949011,0.001866319,0.001699797,0.003028826,0.0003744034],"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":[0.002312062,0.001776728,0.327277,0.0004482173,0.00036544,0.001751436,0.001170561,0.0747152,0.008365281,0.006113334,0.03674027,0.5389646],"study_design_scores_gemma":[0.00003636639,0.0002826337,0.1183834,0.00009479816,0.00008824488,0.0006116565,0.0007515859,0.8630847,0.005212664,0.005556705,0.005840042,0.00005716153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9565709,0.001173908,0.02950322,0.002012494,0.0002758913,0.0001152525,0.004277853,0.00056138,0.005509114],"genre_scores_gemma":[0.9854916,0.0001800737,0.007006058,0.00007453366,0.0001473043,0.00004493808,0.005495385,0.00002969571,0.001530327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004811842,"threshold_uncertainty_score":0.01632273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05870144720319275,"score_gpt":0.2271088946756387,"score_spread":0.1684074474724459,"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."}}