{"id":"W7138885196","doi":"10.1109/globecom59602.2025.11431709","title":"Index Modulation Enhanced NOMA for Opportunistic Spectrum Access","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transmission (telecommunications); Spectral efficiency; Modulation (music); Orthogonal frequency-division multiplexing; Bit error rate; Multiplexing; Benchmark (surveying); Channel access method; Scheme (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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001302233,0.0003577253,0.0004136542,0.000502132,0.0002454099,0.0001688276,0.001371443,0.0003518775,0.000249529],"category_scores_gemma":[0.0003193899,0.0004208441,0.0001225769,0.0008268542,0.0001347414,0.0006071147,0.0005665886,0.0003433144,0.00001897512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004828701,"about_ca_system_score_gemma":0.0001048165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002271667,"about_ca_topic_score_gemma":0.00006795744,"domain_scores_codex":[0.9982399,0.00001521862,0.0006934283,0.0004329499,0.0001352594,0.0004831947],"domain_scores_gemma":[0.9977753,0.0003801499,0.0001551817,0.001501421,0.0001303853,0.00005760409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005069494,0.00007603732,0.0001925046,0.0004256467,0.0001465499,6.2268e-7,0.00003869295,0.3185936,0.005504933,0.3791353,0.000578586,0.2952568],"study_design_scores_gemma":[0.0007212484,0.00003721668,0.002920838,0.0001526523,0.00002365147,4.171254e-7,0.0001582762,0.8077557,0.07738197,0.105926,0.004514598,0.0004074143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003671392,0.0003159443,0.9690912,0.002233776,0.0006762333,0.001124861,0.00003355167,0.001460612,0.02139248],"genre_scores_gemma":[0.9856647,0.001163297,0.008563569,0.00009991911,0.00003709493,0.0003805541,0.00005563494,0.0000536713,0.003981536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9819933,"threshold_uncertainty_score":0.9998243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03094342007450746,"score_gpt":0.3186266422248946,"score_spread":0.2876832221503871,"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."}}