{"id":"W4406857602","doi":"10.1109/access.2025.3534829","title":"An Efficient Frequency Domain Based Attribution and Detection Network","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Frequency domain; Domain (mathematical analysis); Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007363138,0.0009877566,0.0009132887,0.001143926,0.0005089095,0.000734924,0.002001765,0.001017936,0.002556271],"category_scores_gemma":[0.002731616,0.0004359932,0.0004640328,0.0008295852,0.0005975193,0.002355437,0.002169529,0.001229844,0.001034763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00094681,"about_ca_system_score_gemma":0.0006623783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002894259,"about_ca_topic_score_gemma":0.004130134,"domain_scores_codex":[0.9994118,0.00008512284,0.00002664939,0.0001943849,0.0001935595,0.00008843207],"domain_scores_gemma":[0.9990614,0.0002731093,0.00015184,0.0001950758,0.0002614211,0.00005716531],"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":[0.0006367463,0.0003704594,0.00239211,0.0001380187,0.00009802161,0.0002255491,0.0001266555,0.1486195,0.03385823,0.009176631,0.01107389,0.7932842],"study_design_scores_gemma":[0.000009464702,0.00004198649,0.0003626498,0.000006989971,0.00001640698,0.00009480571,0.00001676831,0.9852672,0.009378146,0.003425833,0.001364964,0.0000148454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03344517,0.000460232,0.959793,0.0003896978,0.0001455795,0.00009850568,0.0001819375,0.002952782,0.002533131],"genre_scores_gemma":[0.6785437,0.0004678415,0.3080229,0.0004211102,0.0001709195,0.0001850662,0.0007681013,0.0001517514,0.01126861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002894259,"threshold_uncertainty_score":0.008551538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007439833066486,"score_gpt":0.270124092081019,"score_spread":0.2600496937503541,"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."}}