{"id":"W4232303630","doi":"10.32920/ryerson.14652015","title":"Spam detection system: a new approach based on interval type-2 fuzzy sets","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Spamming; Computer science; The Internet; Interval (graph theory); Filter (signal processing); Forum spam; Fuzzy logic; Set (abstract data type); Artificial intelligence; Spambot; Data mining; Machine learning; World Wide Web; Mathematics; Computer vision","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004757902,0.0003209726,0.0003452121,0.0002596383,0.0001112513,0.000893411,0.0009299685,0.0004185823,0.00003364658],"category_scores_gemma":[0.00009235497,0.0003025657,0.0002200912,0.0004757806,0.00001297055,0.0001951926,0.0006699874,0.000772581,0.0001559388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003349516,"about_ca_system_score_gemma":0.0003734204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160709,"about_ca_topic_score_gemma":0.00009380831,"domain_scores_codex":[0.9976509,0.0002157015,0.000322089,0.001073061,0.0004773553,0.0002609195],"domain_scores_gemma":[0.9980019,0.00006089217,0.0001766897,0.001403721,0.0001940245,0.0001627613],"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":[0.0005203227,0.001295186,0.0002620853,0.005805503,0.0006540748,0.0003797042,0.004856221,0.235718,0.004956582,0.01161792,0.03044975,0.7034847],"study_design_scores_gemma":[0.0002975258,0.0001593927,0.000226256,0.0003628033,0.00003146,0.00006548581,0.00008612119,0.9914112,0.005738944,0.0003187751,0.0008684177,0.0004336173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004016302,0.0000515539,0.9517056,0.0002667666,0.006702681,0.000329382,0.000001284763,0.0009099268,0.03601653],"genre_scores_gemma":[0.9192985,0.000003074447,0.07880402,0.0003919581,0.0004367051,0.00003155749,0.00002686867,0.0000261903,0.0009811539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9152822,"threshold_uncertainty_score":0.9999427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03646633155453138,"score_gpt":0.2513245721095181,"score_spread":0.2148582405549867,"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."}}