{"id":"W7150969612","doi":"10.1109/icaccs54159.2022.11475101","title":"Retraction Notice: Spam Detection for Social Media Networks Using Machine Learning","year":2022,"lang":"","type":"article","venue":"2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS)","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Spambot; The Internet; Support vector machine; Forum spam","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["research_integrity"],"domain":null,"study_design":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00915083,0.002792532,0.001658949,0.003574887,0.003752592,0.006308494,0.004094567,0.0181893,0.01906424],"category_scores_gemma":[0.109871,0.0009708234,0.002392309,0.002074382,0.003808253,0.004865833,0.002003697,0.02617253,0.03536185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00465323,"about_ca_system_score_gemma":0.006230878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008134767,"about_ca_topic_score_gemma":0.006800401,"domain_scores_codex":[0.9902673,0.001622373,0.001470571,0.001257581,0.004726849,0.0006553536],"domain_scores_gemma":[0.904326,0.03706076,0.003910427,0.004538515,0.04588537,0.004278896],"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":[0.00001125193,0.00001036224,0.00007373085,0.00005150199,0.000007031104,0.0000533328,0.00002493646,0.00002242261,0.00006201115,0.0004218916,0.9937387,0.005522876],"study_design_scores_gemma":[0.00003214606,0.00005411454,0.001080476,0.0002959552,0.0000389723,0.0002073736,0.00009764548,0.000991167,0.0004838168,0.001827651,0.9948407,0.00005002301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0003396221,0.001238718,0.00219111,0.3462201,0.6441932,0.0001111083,0.0007332872,0.001015463,0.003957429],"genre_scores_gemma":[0.006817293,0.00494551,0.00628313,0.2874056,0.6049989,0.0005262222,0.0008759825,0.0008148998,0.08733241],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01906424,"threshold_uncertainty_score":0.06377625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07654506074293362,"score_gpt":0.3260327993896142,"score_spread":0.2494877386466806,"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."}}