{"id":"W3037291520","doi":"10.1145/3394231.3397904","title":"Comparing Audience Appreciation to Fact-Checking Across Political Communities on Reddit","year":2020,"lang":"en","type":"article","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Politics; Disinformation; Popularity; Presidential system; Computer science; Typology; Context (archaeology); Presidential election; Fake news; Political communication; Subversion; Political science; Sociology; Media studies; Social media; Internet privacy; World Wide Web; Law; History","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":[],"consensus_categories":[],"category_scores_codex":[0.0003436627,0.00006244486,0.00009882468,0.0000239589,0.0006344347,0.0002283252,0.0002201565,0.00004082851,0.0003553417],"category_scores_gemma":[0.000556798,0.00005827687,0.0000252691,0.0002220005,0.00007902293,0.0003640708,0.00006788006,0.0001141331,0.0004312377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053669,"about_ca_system_score_gemma":0.00004719124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001792215,"about_ca_topic_score_gemma":0.001276107,"domain_scores_codex":[0.9989912,0.00007472801,0.0001556226,0.00006400811,0.0003417185,0.0003727501],"domain_scores_gemma":[0.9993358,0.0001313895,0.00003699786,0.00008918122,0.00005698597,0.0003496477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001799759,0.00001711455,0.002796395,0.000007871242,0.000004522347,2.516094e-7,0.6100942,0.0003372933,0.00002797807,0.3755483,0.006295063,0.004853041],"study_design_scores_gemma":[0.0003314708,0.0001452446,0.03884707,0.00005557328,0.000003525372,3.633835e-7,0.8381971,0.006250017,0.001157762,0.0005192429,0.1141783,0.0003143453],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5317201,0.000001186616,0.00213047,0.009774094,0.00008184306,0.0001070037,0.000003720545,0.0001189712,0.4560626],"genre_scores_gemma":[0.9885833,0.000002584324,0.0002361808,0.01058703,0.0001366027,0.000001125401,0.000004372644,0.000003302794,0.0004454764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4568632,"threshold_uncertainty_score":0.5542832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2248345927423013,"score_gpt":0.4096173623693734,"score_spread":0.1847827696270721,"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."}}