{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005416633,0.00006409016,0.00009683058,0.00006112768,0.0001443555,0.0001793164,0.0002134717,0.0001560601,0.002311778],"category_scores_gemma":[0.0004266147,0.00005432638,0.00006363869,0.00007088186,0.00005742437,0.0000798598,0.0001618012,0.0001592158,0.002555506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006403182,"about_ca_system_score_gemma":0.0002798305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005585239,"about_ca_topic_score_gemma":0.002964873,"domain_scores_codex":[0.9992114,0.0000405814,0.0001519079,0.00008973158,0.0003305175,0.0001758459],"domain_scores_gemma":[0.9995348,0.00003980088,0.00006759865,0.0001499358,0.0000791514,0.000128643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003363743,0.00001776622,0.0001803936,0.00004132108,0.0000341935,0.000002420582,0.1103275,0.00008397979,0.000003412339,0.30879,0.5611945,0.01932127],"study_design_scores_gemma":[0.0001683423,0.000009842174,0.009782762,0.00007572662,0.00001074071,1.532349e-7,0.07169262,0.0002868692,0.00004015065,0.01275066,0.9048638,0.000318385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01004468,0.00001548725,0.0014259,0.01024218,0.00191971,0.000282343,0.00001310026,0.0005225256,0.9755341],"genre_scores_gemma":[0.4488831,0.000411029,0.0003790242,0.002087936,0.000416027,0.000005083139,0.00003684998,0.00001146461,0.5477695],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4388384,"threshold_uncertainty_score":0.9986002,"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."}}