{"id":"W1916447172","doi":"10.48550/arxiv.1001.3403","title":"Real Interference Alignment","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interference alignment; Dirty paper coding; Coding (social sciences); Interference (communication); Computer science; Topology (electrical circuits); Gaussian; Multiplexing; Degenerate energy levels; Data stream mining; Algorithm; Mathematics; Channel (broadcasting); Telecommunications; Precoding; Physics; Combinatorics; MIMO","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":[0.0006726371,0.0007022112,0.0005351724,0.0004320936,0.0007358477,0.001237797,0.0008376508,0.0006628588,0.00578599],"category_scores_gemma":[0.001927378,0.0002401938,0.0003911971,0.0006351062,0.001664492,0.002318975,0.001964203,0.00147577,0.002173179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005290668,"about_ca_system_score_gemma":0.0005259136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000310686,"about_ca_topic_score_gemma":0.0002223937,"domain_scores_codex":[0.9989426,0.0002412115,0.00004806462,0.0002478175,0.0003624787,0.0001578782],"domain_scores_gemma":[0.9990506,0.0002899374,0.000177507,0.0002543725,0.0001710512,0.00005665954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001314492,0.00002708319,0.0004086734,0.0001070152,0.0000216278,0.0001583514,0.0001764726,0.03589441,0.01967331,0.8893679,0.001969901,0.05206382],"study_design_scores_gemma":[0.00004327717,0.0002982203,0.0004754579,0.00007821997,0.00003066467,0.001356943,0.0001881659,0.3997525,0.04111157,0.512521,0.044038,0.0001059448],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02229431,0.0005838444,0.9362364,0.0002983061,0.0002519299,0.00002787279,0.00005943672,0.0002948613,0.03995295],"genre_scores_gemma":[0.7475584,0.001145881,0.2349332,0.0005869687,0.0002937342,0.0001138846,0.0001775848,0.0002000398,0.01499019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00578599,"threshold_uncertainty_score":0.01935613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05730892935754662,"score_gpt":0.1941262029419885,"score_spread":0.1368172735844418,"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."}}