{"id":"W3159905611","doi":"10.18653/v1/2021.nlp4if-1.7","title":"Extractive and Abstractive Explanations for Fact-Checking and Evaluation of News","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; University of Michigan; John Templeton Foundation; National Science Foundation","keywords":"Misinformation; Computer science; Natural language processing; Artificial intelligence; Graph; Information retrieval; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005457338,0.0001131577,0.0001849172,0.00009352089,0.00005226156,0.0001490926,0.0001617355,0.0001181354,0.000009779884],"category_scores_gemma":[0.000168332,0.0001141621,0.00003876666,0.00004100395,0.00001778705,0.0003455046,0.0003759948,0.0001575955,1.259855e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005350136,"about_ca_system_score_gemma":0.0002419338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003168651,"about_ca_topic_score_gemma":0.0001573352,"domain_scores_codex":[0.9988641,0.00005924591,0.0002281004,0.0004683866,0.0002864033,0.00009376493],"domain_scores_gemma":[0.9987012,0.0002651478,0.0002091478,0.0003094108,0.0004775744,0.00003757446],"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":[0.000007290609,0.00008012894,0.0006357376,0.0002142991,0.0001756259,0.000001413577,0.01325027,0.01996991,0.001586379,0.02439182,0.00005263238,0.9396345],"study_design_scores_gemma":[0.000375936,0.00001505596,0.01459421,0.00009890874,0.0000732593,0.000005176616,0.001769581,0.9579321,0.003660807,0.02124088,0.00004394396,0.0001901916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2449848,0.000301189,0.752133,0.0003206102,0.0001722905,0.0004614511,0.000007846183,0.00001947792,0.001599405],"genre_scores_gemma":[0.8166914,0.00004247748,0.1830939,0.00002176558,0.00002812777,0.00007659633,0.0000128262,0.000004265176,0.00002867726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9394443,"threshold_uncertainty_score":0.4655395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1511299951174721,"score_gpt":0.3720213178664477,"score_spread":0.2208913227489755,"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."}}