{"id":"W3163881436","doi":"10.1109/access.2021.3081479","title":"A Spam Transformer Model for SMS Spam Detection","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Transformer; Spamming; Short Message Service; Spambot; Machine learning; Artificial intelligence; Data mining; Computer network; World Wide Web; The Internet; Engineering; Voltage","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":[0.001252741,0.001182413,0.001132858,0.002098043,0.0004371477,0.001060601,0.001573933,0.001263787,0.002151801],"category_scores_gemma":[0.003737957,0.0004026032,0.001040624,0.0009283902,0.0007739725,0.002707686,0.000938631,0.001122507,0.001704309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009922666,"about_ca_system_score_gemma":0.0009468826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003204029,"about_ca_topic_score_gemma":0.002988727,"domain_scores_codex":[0.9993303,0.000177573,0.00004147695,0.0001780265,0.000182162,0.00009059693],"domain_scores_gemma":[0.9988081,0.0004550313,0.0001463394,0.0001318172,0.0003947711,0.00006390548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001904067,0.0007119884,0.02717501,0.0004281231,0.00032373,0.0008519127,0.000393071,0.2838686,0.02904473,0.03518214,0.01600924,0.6041073],"study_design_scores_gemma":[0.00001295771,0.00007537795,0.0005484544,0.000007385875,0.00003660503,0.0001674944,0.00001729339,0.9905244,0.002418119,0.005102872,0.001077569,0.0000115906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05422013,0.0007778676,0.9359179,0.0006478577,0.0001446064,0.000212045,0.0002806081,0.003794104,0.004004837],"genre_scores_gemma":[0.893626,0.0006330743,0.09626205,0.0006392305,0.0002334454,0.0002064225,0.0006294249,0.0001838648,0.007586553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003204029,"threshold_uncertainty_score":0.007199466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05797368719015953,"score_gpt":0.3102206889227196,"score_spread":0.2522470017325601,"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."}}