{"id":"W3154793975","doi":"10.1145/3404835.3463120","title":"Vera: Prediction Techniques for Reducing Harmful Misinformation in Consumer Health Search","year":2021,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Misinformation; Computer science; Credibility; Information retrieval; Relevance (law); Ranking (information retrieval); Context (archaeology); Metric (unit); Data science; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005037041,0.00004573175,0.00007742023,0.00008439271,0.00006405851,0.0000799885,0.0001309326,0.00003259238,0.000008065459],"category_scores_gemma":[0.00003481633,0.00004613885,0.00001986015,0.0001789347,0.000005896462,0.0005148083,0.00006884577,0.00007554173,0.000003595711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000109445,"about_ca_system_score_gemma":0.0002425537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001601231,"about_ca_topic_score_gemma":0.00002560652,"domain_scores_codex":[0.9992623,0.0000327121,0.0002323183,0.0001761978,0.0001294624,0.0001670403],"domain_scores_gemma":[0.9995611,0.00003788595,0.00002986609,0.0002291507,0.0001050036,0.00003701725],"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":[0.000005288883,0.000046445,0.0007190701,0.0001425377,0.00000622421,0.000002018708,0.00432864,0.00134005,0.001316922,0.03692727,0.003226553,0.951939],"study_design_scores_gemma":[0.0002431518,0.00004060941,0.0006321828,0.00007090318,6.288256e-7,0.0000139319,0.0001786766,0.9597205,0.0340558,0.001018462,0.003952957,0.00007220103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008969855,0.00007742365,0.9852792,0.003621174,0.0001416474,0.0002321679,0.000001698794,0.0001632133,0.001513604],"genre_scores_gemma":[0.4133445,0.00005503714,0.5853966,0.0007736585,0.00004777703,0.00002595039,0.00001278655,0.000004084589,0.0003395391],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9583805,"threshold_uncertainty_score":0.1881488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04702965344254133,"score_gpt":0.3218547508486092,"score_spread":0.2748250974060678,"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."}}