{"id":"W2252350410","doi":"10.1002/pra2.2015.145052010083","title":"Deception detection for news: Three types of fakes","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":544,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; Government of Canada","keywords":"Vetting; Deception; Fake news; Computer science; Internet privacy; Disinformation; Data science; Social media; World Wide Web; Computer security; Political science; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00592775,0.0007097797,0.001015947,0.00536254,0.002727857,0.004642198,0.001018435,0.00276194,0.002640979],"category_scores_gemma":[0.06971049,0.000527368,0.000834035,0.003125269,0.002750675,0.004826812,0.002350623,0.001995631,0.0009685696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243623,"about_ca_system_score_gemma":0.0005459472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656028,"about_ca_topic_score_gemma":0.001164706,"domain_scores_codex":[0.9885228,0.003329352,0.001412142,0.00112278,0.004922982,0.0006901036],"domain_scores_gemma":[0.8669606,0.08348106,0.01856619,0.01780226,0.01149926,0.001690592],"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":[0.005601092,0.0011432,0.4233256,0.002313185,0.0004633405,0.0101161,0.01793971,0.009817447,0.02166732,0.04351357,0.0204163,0.4436832],"study_design_scores_gemma":[0.0002655272,0.001846728,0.4529537,0.001956605,0.0009596974,0.03574385,0.01246893,0.2474372,0.1150444,0.05792407,0.07268122,0.0007179676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9270408,0.002528373,0.04330077,0.002978489,0.0004049047,0.0004957669,0.00226774,0.0007728581,0.02021029],"genre_scores_gemma":[0.9800511,0.0004548791,0.01521028,0.0002788558,0.0001632608,0.0001007505,0.001010647,0.00007025837,0.002660055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00592775,"threshold_uncertainty_score":0.03134936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01534788402570559,"score_gpt":0.2358418938291395,"score_spread":0.2204940098034339,"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."}}