{"id":"W4407938106","doi":"10.1109/tcomm.2025.3545678","title":"Predictive Beamforming Approach for Secure Integrated Sensing and Communication With Multiple Aerial Eavesdroppers","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Memorial University of Newfoundland","funders":"","keywords":"Beamforming; Computer science; Computer network; Telecommunications","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":[0.0004503141,0.000915421,0.000607998,0.000265897,0.0003559518,0.000602035,0.0008339424,0.0007041804,0.001822155],"category_scores_gemma":[0.001176408,0.0003882952,0.0005301163,0.000538617,0.0006765205,0.0009977168,0.001067073,0.00143515,0.0005392637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004212045,"about_ca_system_score_gemma":0.0008815386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002852525,"about_ca_topic_score_gemma":0.002937434,"domain_scores_codex":[0.999602,0.00008439636,0.00001591566,0.00008712946,0.0001459414,0.00006457252],"domain_scores_gemma":[0.9995949,0.0002131653,0.0000459919,0.00004086233,0.00008699583,0.0000181521],"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":[0.0001525918,0.00003240479,0.000667006,0.000138253,0.00007331631,0.0002783154,0.0001758596,0.8126452,0.02053375,0.03997076,0.002434238,0.1228983],"study_design_scores_gemma":[0.000005023218,0.00003592218,0.00006374544,0.000006140558,0.00001039754,0.0000363656,0.00001330426,0.9938679,0.001579521,0.003817724,0.0005565451,0.000007419115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004511505,0.0001892244,0.9934628,0.00009655711,0.00002702514,0.00001045922,0.00002666262,0.0001205687,0.00155529],"genre_scores_gemma":[0.7638612,0.001217851,0.2258738,0.0003588232,0.0001320939,0.000195275,0.0002445764,0.00005505648,0.00806119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002852525,"threshold_uncertainty_score":0.006095707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110921058264578,"score_gpt":0.2247702684579384,"score_spread":0.2136781626314806,"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."}}