{"id":"W4251960172","doi":"10.31219/osf.io/p8su6","title":"People are worse at detecting fake news in their foreign language","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Reflection (computer programming); Immigration; Context (archaeology); Fake news; Cognition; Psychology; Foreign language; Advertising; Cognitive psychology; Computer science; Political science; Internet privacy; History; Business; Law","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006333226,0.0001549435,0.0002600766,0.0001237281,0.000232996,0.0002962816,0.0002742803,0.0002718568,0.004103796],"category_scores_gemma":[0.0009585915,0.0001324978,0.0001152164,0.0002941847,0.00003214502,0.0002179034,0.0004273038,0.0003623744,0.00007550006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002852087,"about_ca_system_score_gemma":0.0002742424,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01656746,"about_ca_topic_score_gemma":0.5249543,"domain_scores_codex":[0.9986895,0.0001555509,0.000291824,0.0002108593,0.0003029234,0.0003493372],"domain_scores_gemma":[0.9991627,0.0001345284,0.0002081252,0.0002868775,0.00006112262,0.0001466905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00000884249,0.00003090356,0.01072069,0.00009045882,0.00001648827,0.00001356961,0.9502795,0.0002757125,0.00003764094,0.001022545,0.002120208,0.03538345],"study_design_scores_gemma":[0.0001782616,0.00000442295,0.01216779,0.0001536123,0.000004253584,0.000001413735,0.9825247,0.0004045701,0.0004562312,0.0002848491,0.003558921,0.0002609611],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6762323,0.0001106734,0.0001694096,0.0003840225,0.0002013452,0.0002280465,0.000006242724,0.0000862799,0.3225816],"genre_scores_gemma":[0.9902691,0.0001263399,0.0003325509,0.0006665469,0.000154054,0.000006169351,0.00002922361,0.00001061902,0.00840545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5083868,"threshold_uncertainty_score":0.9968066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0371218838830084,"score_gpt":0.3137693264267606,"score_spread":0.2766474425437522,"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."}}