{"id":"W4388093192","doi":"10.48550/arxiv.2310.19141","title":"Optical STAR-RIS-Aided VLC Systems: RSMA Versus NOMA","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; York University","funders":"","keywords":"Visible light communication; Computer science; Maximization; Optical wireless; Heuristic; Transmission (telecommunications); Optimization problem; Electronic engineering; Wireless; Mathematical optimization; Algorithm; Optics; Telecommunications; Physics; Artificial intelligence; Engineering; Mathematics","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":[0.0006089503,0.0005766642,0.0007297165,0.0003297661,0.000372669,0.001158016,0.0007778644,0.0006108452,0.0008508388],"category_scores_gemma":[0.0009117189,0.0002145432,0.0003493223,0.0006340931,0.0005972918,0.0005636482,0.0007167271,0.0005168533,0.0002344823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005962666,"about_ca_system_score_gemma":0.0009867916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002352734,"about_ca_topic_score_gemma":0.003396283,"domain_scores_codex":[0.9993914,0.0002546079,0.00001745495,0.00008707249,0.0001435965,0.0001058388],"domain_scores_gemma":[0.9994857,0.0002283033,0.0001153444,0.00004424755,0.00009378532,0.00003259344],"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":[0.0002546226,0.00009760977,0.0008393109,0.0001580035,0.00007631383,0.0002300942,0.0001108107,0.8938924,0.01854543,0.01755886,0.001087549,0.06714895],"study_design_scores_gemma":[0.000009178293,0.0001044185,0.0001085414,0.000005658758,0.00001255999,0.00005397141,0.00002665223,0.9963967,0.00188032,0.0008962576,0.0004970991,0.000008538133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1173765,0.002379069,0.8633643,0.0004442029,0.0001137251,0.00008198877,0.00004956857,0.0002853497,0.01590521],"genre_scores_gemma":[0.9479765,0.0005155489,0.04925504,0.00008873994,0.00004956155,0.00004251771,0.00002156031,0.0000142014,0.002036284],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002352734,"threshold_uncertainty_score":0.004678011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431332982027098,"score_gpt":0.1986257672576864,"score_spread":0.05549246905497665,"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."}}