{"id":"W2970675344","doi":"10.14778/3352063.3352117","title":"Combating fake news","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Disinformation; Fake news; Crowdsourcing; Social media; Popularity; Internet privacy; Misinformation; Computer science; News media; Political science; Journalism; Public relations; Data science; World Wide Web; Sociology; Media studies; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004560047,0.00005674142,0.00008932942,0.00003222952,0.0001640769,0.0000665053,0.0003033829,0.00003198249,0.0003498082],"category_scores_gemma":[0.0002331117,0.00003802374,0.00005547475,0.0001927002,0.00005407652,0.0002999257,0.00007333643,0.00006706523,0.00009141034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005881797,"about_ca_system_score_gemma":0.00004281153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003075203,"about_ca_topic_score_gemma":0.00002225733,"domain_scores_codex":[0.9991493,0.000005762069,0.0001738802,0.00006914925,0.000417152,0.0001847968],"domain_scores_gemma":[0.9995641,0.00002442267,0.0001908547,0.00005419411,0.0001061103,0.00006036405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002631726,0.0001051618,0.04878106,0.0001463079,0.00004141745,3.838238e-8,0.1705216,0.00001398267,0.01651036,0.6975129,0.04193233,0.02440849],"study_design_scores_gemma":[0.001958748,0.0001936354,0.02492262,0.0003730014,0.00004105499,0.00000272593,0.2175608,0.0003198518,0.07410217,0.01255817,0.6674601,0.0005071997],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5593018,0.00001091543,0.00000138232,0.00279239,0.0001903826,0.0002737669,8.399733e-7,0.00002399399,0.4374045],"genre_scores_gemma":[0.9937443,0.00002614091,0.0002318646,0.0006376263,0.00005278235,0.000001891003,2.049206e-7,0.000003850151,0.00530131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6849548,"threshold_uncertainty_score":0.3830155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01544656451373473,"score_gpt":0.2722623878711316,"score_spread":0.2568158233573969,"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."}}