{"id":"W4407374643","doi":"10.1109/tcomm.2025.3541092","title":"Robust and Secure Multi-User STAR-RIS-Aided Communications: Optimization Versus Machine Learning","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Space Satellite Systems and Control","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Canada Excellence Research Chairs, Government of Canada; National Science and Technology Council; Canada Research Chairs","keywords":"Computer science; Star (game theory); Robustness (evolution); Electronic engineering; Engineering; Physics","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":[0.000987472,0.001020229,0.001236089,0.0002931785,0.0002673464,0.001162316,0.0008056071,0.001005336,0.00131333],"category_scores_gemma":[0.002433702,0.0004484565,0.0004940171,0.0005631684,0.001048216,0.001020218,0.001109602,0.001300035,0.0004283419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006715319,"about_ca_system_score_gemma":0.001246163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00263581,"about_ca_topic_score_gemma":0.002223246,"domain_scores_codex":[0.9993155,0.0002650361,0.00002599273,0.0001294814,0.0001664029,0.00009754459],"domain_scores_gemma":[0.9987327,0.0008120594,0.0001728214,0.0001044628,0.0001329233,0.00004493366],"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":[0.00005045404,0.00002440329,0.0002388362,0.00004516844,0.00002538816,0.00004233566,0.00002157857,0.9707399,0.001301541,0.007682245,0.0003628754,0.01946523],"study_design_scores_gemma":[0.000002354369,0.00001669248,0.00002371272,0.000002236665,0.000002161941,0.000006494926,0.000003038782,0.9984603,0.0002881699,0.001093225,0.00009933901,0.000002297519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0157639,0.0004966454,0.9799685,0.0002802003,0.00002694026,0.00002222717,0.00002913296,0.0002294927,0.003182895],"genre_scores_gemma":[0.8884732,0.0006083516,0.1068833,0.0002125511,0.00007459919,0.00008636246,0.00009489756,0.00005802621,0.00350868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00263581,"threshold_uncertainty_score":0.005240977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03455601189354794,"score_gpt":0.2572922130072263,"score_spread":0.2227362011136784,"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."}}