{"id":"W2410465342","doi":"10.1002/pra2.2015.145052010082","title":"Automatic deception detection: Methods for finding fake news","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":982,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; Government of Canada","keywords":"Deception; Vetting; Fake news; Computer science; Flagging; Certainty; Typology; Data science; Artificial intelligence; Internet privacy; Computer security; Psychology; Social psychology","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":[0.003854168,0.0008910957,0.001175328,0.004662829,0.0008723955,0.002665414,0.002235619,0.00212078,0.002818868],"category_scores_gemma":[0.02769058,0.0004839944,0.0006027403,0.001776125,0.001297899,0.003518605,0.001642291,0.001715222,0.001364233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008468937,"about_ca_system_score_gemma":0.0005930346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133964,"about_ca_topic_score_gemma":0.001125504,"domain_scores_codex":[0.9971163,0.001079274,0.000189483,0.0006047111,0.0008179393,0.0001923631],"domain_scores_gemma":[0.9771916,0.01411318,0.002887426,0.002566872,0.002870067,0.0003708776],"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":[0.0005941485,0.0003196974,0.0174356,0.0004537765,0.0001617362,0.000258979,0.0005778613,0.04868676,0.01536454,0.02199763,0.007146869,0.8870024],"study_design_scores_gemma":[0.00002064617,0.00006154803,0.003737692,0.0000442159,0.00003097189,0.0002949452,0.0001430007,0.9658933,0.009348151,0.01783921,0.00254481,0.00004151648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04482771,0.0009651128,0.948031,0.0006891052,0.0001413459,0.0001393367,0.0002515845,0.001582823,0.00337198],"genre_scores_gemma":[0.6690608,0.0005469008,0.3247871,0.0001747432,0.0003513858,0.000161634,0.0004471127,0.0001477647,0.004322472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004662829,"threshold_uncertainty_score":0.02038306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04342581138251546,"score_gpt":0.3799104506309118,"score_spread":0.3364846392483963,"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."}}