{"id":"W4409391137","doi":"10.22214/ijraset.2025.68420","title":"CyberSleuth AI: Intelligent Network Forensics Analyzer","year":2025,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Network forensics; Spectrum analyzer; Computer security; Digital forensics; Telecommunications","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":[0.0007584232,0.00126026,0.0004169883,0.003528654,0.0008264037,0.001505972,0.00142248,0.0006747725,0.02413286],"category_scores_gemma":[0.002054125,0.0003295492,0.000244243,0.001041346,0.0005110034,0.00170329,0.00120137,0.0008461964,0.006861249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158805,"about_ca_system_score_gemma":0.002491855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01563717,"about_ca_topic_score_gemma":0.01390537,"domain_scores_codex":[0.9994629,0.00005098597,0.0000352,0.0001296637,0.0002505411,0.00007073302],"domain_scores_gemma":[0.9990207,0.0002027821,0.00009282759,0.000167643,0.0004332703,0.00008279123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001527617,0.0006631131,0.01822973,0.0005231358,0.0001594162,0.0008854549,0.0008657522,0.01904333,0.09213265,0.020079,0.2389965,0.6068943],"study_design_scores_gemma":[0.0001992913,0.0002264562,0.01698884,0.0001051549,0.00009148653,0.001057387,0.000384361,0.6591477,0.153698,0.01502121,0.1529279,0.0001522803],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.1179404,0.0006856578,0.3218684,0.001635353,0.0002829696,0.001066804,0.01275827,0.4539195,0.08984274],"genre_scores_gemma":[0.6863676,0.0003168934,0.2517087,0.001161015,0.0001196631,0.0005771606,0.01486348,0.003823915,0.04106178],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02413286,"threshold_uncertainty_score":0.08073252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03286767714990576,"score_gpt":0.3619171572369957,"score_spread":0.32904948008709,"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."}}