{"id":"W4295855143","doi":"10.3390/bdcc6030093","title":"Hierarchical Co-Attention Selection Network for Interpretable Fake News Detection","year":2022,"lang":"en","type":"article","venue":"Big Data and Cognitive Computing","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Social Science Fund of China","keywords":"Computer science; Selection (genetic algorithm); Interpretability; Sentence; Key (lock); Artificial intelligence; Fake news; Word (group theory); Social media; Event (particle physics); Natural language processing; Machine learning; Linguistics; World Wide Web; Internet privacy","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":[0.001323705,0.001013651,0.0007027207,0.001367259,0.0005479452,0.0006338491,0.001255641,0.001209178,0.00170682],"category_scores_gemma":[0.004625813,0.000408061,0.0007298586,0.0007366455,0.0007057061,0.001213649,0.0007710647,0.001421846,0.0002849184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515895,"about_ca_system_score_gemma":0.0007457798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01142159,"about_ca_topic_score_gemma":0.01099247,"domain_scores_codex":[0.9994598,0.00017718,0.00002227152,0.0001752392,0.00008293495,0.00008262959],"domain_scores_gemma":[0.9981226,0.001166754,0.0002275618,0.0000917266,0.0003067659,0.00008453378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00107322,0.0004238086,0.02860978,0.000212316,0.0003813409,0.0008153574,0.0006787599,0.6513946,0.008388682,0.01938799,0.008901979,0.279732],"study_design_scores_gemma":[0.000005880916,0.00001865256,0.001178806,0.000006963463,0.00002197449,0.00002846768,0.00001069208,0.9945062,0.0004353487,0.003611769,0.0001686774,0.000006502364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3367887,0.002261776,0.648001,0.002892765,0.0002578016,0.0001937147,0.0006678668,0.001358564,0.007577691],"genre_scores_gemma":[0.9744333,0.0002743804,0.02163614,0.0002581263,0.0001249541,0.00008252393,0.0003084834,0.00002488277,0.002857159],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01142159,"threshold_uncertainty_score":0.0227102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0896688239505401,"score_gpt":0.354268678516176,"score_spread":0.2645998545656359,"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."}}