{"id":"W3173838993","doi":"","title":"Overview of the TREC 2020 Health Misinformation Track.","year":2020,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Misinformation; Track (disk drive); Computer science; Information retrieval; Data science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01593824,0.001940425,0.00140445,0.02173156,0.002696482,0.008695533,0.002880062,0.002478431,0.05403712],"category_scores_gemma":[0.01326886,0.0006940336,0.001190364,0.01497256,0.0008488221,0.007179159,0.002661017,0.002513537,0.03912666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007022777,"about_ca_system_score_gemma":0.01817399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1078189,"about_ca_topic_score_gemma":0.2165781,"domain_scores_codex":[0.9938671,0.001269178,0.0004136892,0.0003670145,0.003446485,0.0006364513],"domain_scores_gemma":[0.9700852,0.003965015,0.001725141,0.001185007,0.01873118,0.004308484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005902556,0.00006111777,0.0003431033,0.000977296,0.0000265558,0.00002257106,0.00004698717,0.0002962097,0.0009723405,0.0007745069,0.925262,0.07115819],"study_design_scores_gemma":[0.00004943596,0.0001540869,0.004134604,0.0009695716,0.00009366894,0.00009494867,0.0001751856,0.001314565,0.00227573,0.001776225,0.988865,0.00009704526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.008467169,0.1925066,0.02523356,0.1002153,0.03140583,0.005513674,0.3015836,0.01791935,0.3171549],"genre_scores_gemma":[0.02991194,0.1051057,0.06758911,0.02325463,0.01503808,0.003471215,0.4563071,0.003302035,0.2960202],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.1078189,"threshold_uncertainty_score":0.2143826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1556287675719629,"score_gpt":0.3753961097522171,"score_spread":0.2197673421802542,"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."}}