{"id":"W4388930684","doi":"10.21203/rs.3.rs-3626868/v1","title":"Meta Learning for Enhanced Web Security Against Malicious URLs","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Machine learning; Classifier (UML); Artificial intelligence; Random forest; Internet security; Support vector machine; Gradient boosting; Network security; The Internet; Data mining; Information security; Computer security; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003222544,0.001279002,0.001779175,0.00225437,0.0006226425,0.001676567,0.001519697,0.001547866,0.001626017],"category_scores_gemma":[0.00561783,0.0004057997,0.001628731,0.0008875355,0.000563541,0.002290747,0.00110767,0.001696927,0.0008978205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001160965,"about_ca_system_score_gemma":0.001030357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002655675,"about_ca_topic_score_gemma":0.002566856,"domain_scores_codex":[0.9989152,0.0003413777,0.00007050647,0.0002122273,0.0002729987,0.0001876498],"domain_scores_gemma":[0.9971809,0.001404905,0.0003610666,0.0003266064,0.000580807,0.0001457727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009215531,0.0008287715,0.01022784,0.000257557,0.000385745,0.0002214164,0.0001055413,0.5756863,0.009859703,0.003533034,0.007198934,0.3907735],"study_design_scores_gemma":[0.00001227167,0.0001051652,0.0005459355,0.00002157837,0.00004279683,0.00003659089,0.00001683483,0.9949312,0.002087689,0.00168575,0.0005046452,0.000009574286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2998036,0.007482466,0.6693482,0.002046035,0.0006982321,0.0003423418,0.0008174151,0.01130481,0.008156918],"genre_scores_gemma":[0.9210555,0.0005647941,0.07429121,0.0004039736,0.0001536136,0.000109772,0.0007585218,0.0001599594,0.002502631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003222544,"threshold_uncertainty_score":0.01704264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1737066090430595,"score_gpt":0.4081832764903918,"score_spread":0.2344766674473323,"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."}}