{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01263258,0.002063584,0.001097132,0.0108256,0.001163733,0.004507612,0.001976012,0.001883517,0.005789052],"category_scores_gemma":[0.08581514,0.0007578987,0.001644816,0.003437883,0.001719674,0.007998449,0.002595092,0.002708786,0.002304682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530412,"about_ca_system_score_gemma":0.00271555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002800013,"about_ca_topic_score_gemma":0.006027083,"domain_scores_codex":[0.9839474,0.008852696,0.001107788,0.001920347,0.003841063,0.0003307366],"domain_scores_gemma":[0.8873005,0.08487236,0.006724075,0.01102307,0.009094308,0.0009857623],"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":[0.001187807,0.0006112031,0.02104087,0.00277205,0.0004685448,0.0008724366,0.005520923,0.02640179,0.01900162,0.05926936,0.02344751,0.839406],"study_design_scores_gemma":[0.0003275981,0.0004981451,0.01112312,0.000560079,0.0004930865,0.0009549124,0.002759607,0.716718,0.07389371,0.1211657,0.07122006,0.0002860339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03995496,0.001254433,0.9322692,0.001506042,0.0001542254,0.0007716641,0.00518726,0.01557896,0.003323249],"genre_scores_gemma":[0.2152015,0.0003922042,0.7709428,0.000167955,0.0002116011,0.0003812945,0.01054292,0.0007586766,0.001401077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01263258,"threshold_uncertainty_score":0.06680828,"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."}}