{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001062398,0.00006182862,0.00008272482,0.00005670818,0.002067073,0.000151058,0.0001230498,0.00002967681,0.00004006751],"category_scores_gemma":[0.0004032846,0.00006801219,0.00002158384,0.0002420791,0.00005202708,0.00028618,0.0001666053,0.0001392856,0.000003904579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003827027,"about_ca_system_score_gemma":0.00007359619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001547092,"about_ca_topic_score_gemma":0.0003558963,"domain_scores_codex":[0.9990231,0.000205321,0.0001702595,0.0001850866,0.0001831799,0.0002329872],"domain_scores_gemma":[0.9994561,0.0002322435,0.0001091184,0.00006127392,0.00007149546,0.00006978765],"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":[0.0000560531,0.00001739304,0.001004268,0.000008937115,0.00001566136,1.710626e-7,0.003358638,0.00002970386,0.00007531991,0.0005072408,0.001552717,0.9933739],"study_design_scores_gemma":[0.002647766,0.0006900985,0.02948232,0.0001592795,0.0001572364,0.00003387792,0.07807475,0.5253634,0.0001905857,0.002871112,0.3596427,0.0006868437],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2552089,0.00005457238,0.7375777,0.0002040823,0.0006947393,0.000437202,0.0001687529,0.00007965197,0.005574429],"genre_scores_gemma":[0.9980764,0.00001541469,0.0002519387,0.0005427256,0.000523381,0.00000484767,0.0003989089,0.000005337627,0.0001810961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.992687,"threshold_uncertainty_score":0.9992321,"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."}}