{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004995244,0.0003001188,0.0005165298,0.0006636086,0.0006426938,0.0009612688,0.001996959,0.0004453233,0.00002289869],"category_scores_gemma":[0.001343479,0.00028648,0.0004954601,0.0009123585,0.00007980299,0.0002343485,0.002872672,0.002545665,0.0002547341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253573,"about_ca_system_score_gemma":0.0005073131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002851819,"about_ca_topic_score_gemma":0.0002079232,"domain_scores_codex":[0.9952363,0.0008883039,0.0003580332,0.001247819,0.00133729,0.0009321969],"domain_scores_gemma":[0.9962265,0.001275316,0.0001504749,0.001278282,0.0008476134,0.0002218147],"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":[0.001021315,0.00199236,0.001752077,0.03502034,0.01674949,0.0009007139,0.08550885,0.2013761,0.1058038,0.07192586,0.1774935,0.3004556],"study_design_scores_gemma":[0.001472091,0.001338414,0.0009889101,0.001313504,0.0002806822,0.000008437416,0.000554477,0.6780178,0.04696119,0.1571033,0.110015,0.001946228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2341735,0.004260232,0.7208586,0.009909276,0.007616318,0.008445394,0.0002572162,0.005781863,0.008697663],"genre_scores_gemma":[0.9918244,0.0005658763,0.002341198,0.00005045262,0.0006480039,0.001308257,0.00009465119,0.00006557402,0.003101606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7576509,"threshold_uncertainty_score":0.9999588,"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."}}