{"id":"W3012209663","doi":"10.1145/3378422","title":"Detecting fake news in social media","year":2020,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Citation; Social media; Perspective (graphical); Library science; Advertising; Media studies; History; Computer science; World Wide Web; Political science; Sociology; Business; Artificial intelligence","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":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.0003239731,0.00002716339,0.00005914936,0.00002217524,0.0004271423,0.00002102676,0.008101711,0.00003261512,0.00004359868],"category_scores_gemma":[0.03829539,0.00002242851,0.00003504048,0.0004107875,0.0001770939,0.0001346271,0.002673403,0.0001254774,0.00002014479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002525617,"about_ca_system_score_gemma":0.00008737214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002656651,"about_ca_topic_score_gemma":0.003782702,"domain_scores_codex":[0.9994158,0.0001886063,0.0001548184,0.00003014257,0.0001300657,0.00008060141],"domain_scores_gemma":[0.9969269,0.0003448701,0.0001027364,0.002549328,0.00003989597,0.00003626831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000006281196,0.00003530298,0.003005759,0.000007992775,0.000007141603,2.680047e-8,0.8740219,0.00001244587,0.0003784386,0.04522485,0.03985218,0.03744766],"study_design_scores_gemma":[0.000961247,0.00001820021,0.1019675,0.00006930528,0.00002405875,3.623815e-7,0.4051214,0.0007249003,0.001109746,0.09853824,0.3911661,0.0002988247],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2781396,0.0001631267,0.00001250712,0.5494589,0.00009644052,0.0002082872,0.000006201916,0.00004912166,0.1718658],"genre_scores_gemma":[0.9962662,0.00009162739,0.002668017,0.0008996163,0.00004464607,0.00000113131,0.0000011819,0.000002183299,0.00002543881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7181265,"threshold_uncertainty_score":0.9972649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2110286405164313,"score_gpt":0.387276143825238,"score_spread":0.1762475033088067,"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."}}