{"id":"W7118676423","doi":"10.1109/vtc2025-fall65116.2025.11310478","title":"Improving SAGIN Resilience to Jamming with Reconfigurable Intelligent Surfaces","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université de Montréal; Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Jamming; Geostationary orbit; Beamforming; Resilience (materials science); Interference (communication); Satellite; Channel (broadcasting); Low earth orbit; Signal-to-noise ratio (imaging)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003086112,0.000422533,0.0004323921,0.0005036141,0.0002987811,0.0001924853,0.001435559,0.0001945302,0.0001798309],"category_scores_gemma":[0.0003943937,0.000405443,0.0000512314,0.001745728,0.0001791017,0.000427743,0.0004126544,0.0006430426,0.0001372098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004328667,"about_ca_system_score_gemma":0.0001298589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003776783,"about_ca_topic_score_gemma":0.0005060417,"domain_scores_codex":[0.9978016,0.0000428427,0.0006407383,0.00060682,0.0002092044,0.0006988021],"domain_scores_gemma":[0.9973791,0.0003801134,0.0001061869,0.001848486,0.0001781972,0.0001079074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002765262,0.00002420891,0.0003875101,0.0001831601,0.00005081267,0.000002578195,0.000315998,0.4958097,0.02048785,0.007355351,0.0002037341,0.4751514],"study_design_scores_gemma":[0.0002425429,0.000181108,0.000310031,0.001111774,0.00002534744,0.000003287863,0.0102441,0.128386,0.8428166,0.0007885979,0.01517067,0.000719953],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05418478,0.004430953,0.8894512,0.002422599,0.0003140507,0.0007838268,0.000004190547,0.001599073,0.04680933],"genre_scores_gemma":[0.8614231,0.001580581,0.1287032,0.000131626,0.000007239416,0.0000862048,0.000001494623,0.00004203095,0.008024524],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8223287,"threshold_uncertainty_score":0.9998397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032072716668972,"score_gpt":0.2460278366772858,"score_spread":0.2357071095105961,"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."}}