{"id":"W4376277091","doi":"10.36227/techrxiv.22795130.v1","title":"Fake Content","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Social media; Credibility; Ground truth; Benchmark (surveying); Cluster analysis; Artificial intelligence; Baseline (sea); Information retrieval; Machine learning; Fake news; Fraction (chemistry); Data mining; World Wide Web; Internet privacy; Geography","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":[0.00132513,0.001127968,0.000982995,0.00390154,0.001617304,0.002704312,0.0008590856,0.001503743,0.008697625],"category_scores_gemma":[0.01609882,0.0004510435,0.0006847979,0.002231133,0.0008636465,0.004382678,0.001347652,0.001023033,0.007381772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259857,"about_ca_system_score_gemma":0.0008531672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002247594,"about_ca_topic_score_gemma":0.00270117,"domain_scores_codex":[0.9966589,0.0004228984,0.000239253,0.000604302,0.001739978,0.0003346075],"domain_scores_gemma":[0.9837576,0.005386658,0.002892346,0.004363139,0.003291112,0.0003092306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001537426,0.0004092901,0.1090794,0.003495141,0.0003853596,0.002809116,0.001883366,0.009403628,0.04657248,0.02530506,0.1186386,0.6804811],"study_design_scores_gemma":[0.00009684332,0.0007077655,0.1626617,0.001619991,0.000432304,0.01093894,0.00254268,0.2344607,0.1919091,0.0311377,0.363139,0.0003533831],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6715313,0.006875373,0.1335257,0.003998638,0.001909147,0.001695849,0.04527409,0.01705102,0.1181388],"genre_scores_gemma":[0.9022815,0.001400191,0.05308314,0.0006852517,0.00041135,0.0003824481,0.01717543,0.0005951631,0.02398551],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008697625,"threshold_uncertainty_score":0.02909648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4517153759178928,"score_gpt":0.4212893299144946,"score_spread":0.03042604600339816,"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."}}