{"id":"W4408324703","doi":"10.1109/globecom52923.2024.10901459","title":"Predictive Beamforming Approach for Secure Integrated Sensing and Communication","year":2024,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":1,"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":[0.0006125931,0.0009920733,0.0006325916,0.0003162635,0.0002826974,0.0006549194,0.0008399292,0.0007627538,0.002205428],"category_scores_gemma":[0.001226085,0.0004061532,0.0004355648,0.0006579465,0.0006576558,0.0009703217,0.0009416142,0.001121993,0.0005701478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005010417,"about_ca_system_score_gemma":0.0008440712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001961704,"about_ca_topic_score_gemma":0.002064826,"domain_scores_codex":[0.9995659,0.0001209372,0.00001373546,0.00007756147,0.0001667252,0.00005522896],"domain_scores_gemma":[0.9995994,0.0002311144,0.00003923614,0.00003841015,0.00007645286,0.0000153897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005852755,0.00002033332,0.0002791924,0.00008982851,0.00004204183,0.00009428124,0.00004909426,0.8777661,0.006465528,0.05020961,0.001388535,0.06353692],"study_design_scores_gemma":[0.000004067188,0.00003532426,0.00004567055,0.000006287686,0.000008275765,0.00002808483,0.00000754013,0.9909696,0.0007821906,0.007314892,0.0007921184,0.000005885536],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001785793,0.000211341,0.9961106,0.00006602625,0.00002009338,0.000008655756,0.00001935263,0.00006421792,0.001713893],"genre_scores_gemma":[0.6777983,0.001789875,0.3109079,0.0003223732,0.0001778873,0.0002210748,0.0002261304,0.00006822457,0.008488094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002205428,"threshold_uncertainty_score":0.007377923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008427010219974192,"score_gpt":0.2001919698030216,"score_spread":0.1917649595830475,"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."}}