{"id":"W4412530720","doi":"10.3390/electronics14142917","title":"FIGS: A Realistic Intrusion-Detection Framework for Highly Imbalanced IoT Environments","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Internet of Things; Intrusion detection system; Computer science; Intrusion; Geology; Artificial intelligence; Computer security; Geochemistry","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":[0.001580442,0.001029824,0.0005928145,0.0006715143,0.0002770746,0.0006907909,0.001696137,0.0009551542,0.0009836728],"category_scores_gemma":[0.003763287,0.0003806057,0.0008072917,0.0003375655,0.0006455677,0.00116006,0.001316323,0.001545903,0.0003108114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007850862,"about_ca_system_score_gemma":0.000565667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002690547,"about_ca_topic_score_gemma":0.004441984,"domain_scores_codex":[0.9993887,0.0002108356,0.00002147098,0.0001516706,0.0001705034,0.00005682084],"domain_scores_gemma":[0.9991572,0.0004123624,0.0001042495,0.0001147176,0.0001667694,0.00004471081],"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":[0.0001717161,0.000117635,0.004801916,0.00006226866,0.00008506954,0.0001399041,0.00008919378,0.9047614,0.006276333,0.007358481,0.005479635,0.0706564],"study_design_scores_gemma":[0.000004100702,0.00001885098,0.0002453195,0.000002666391,0.000003370711,0.00003302222,0.000004444665,0.9964994,0.0006514197,0.002037304,0.0004959416,0.00000412349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03285643,0.0002837695,0.9615316,0.0003907252,0.0001018423,0.0001477171,0.0004213871,0.0028879,0.001378536],"genre_scores_gemma":[0.6974159,0.0003061529,0.2960922,0.0005553974,0.0001441414,0.0003221411,0.001825505,0.0002910329,0.003047513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002690547,"threshold_uncertainty_score":0.0083583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006680318616366729,"score_gpt":0.240782208063013,"score_spread":0.2341018894466463,"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."}}