{"id":"W4402746541","doi":"10.36227/techrxiv.172710264.41398642/v1","title":"Tensor Signal Modelling and Channel Estimation for Reconfigurable Intelligent Surface-Assisted Full-Duplex MIMO","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"MIMO; Duplex (building); SIGNAL (programming language); Channel (broadcasting); Tensor (intrinsic definition); Computer science; Surface (topology); Electronic engineering; Telecommunications; Engineering; Mathematics; Geometry; Chemistry","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":[0.0005239854,0.0008612325,0.0004940964,0.0003345917,0.0002294804,0.0007592421,0.0005129928,0.0006264314,0.0008831838],"category_scores_gemma":[0.002196616,0.0003548356,0.0005497691,0.0004373215,0.0006797788,0.001236985,0.0007469531,0.001174907,0.000497819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003714067,"about_ca_system_score_gemma":0.0008655904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003278449,"about_ca_topic_score_gemma":0.003291972,"domain_scores_codex":[0.9995913,0.0001472751,0.00001574858,0.0000698976,0.0001359894,0.0000398894],"domain_scores_gemma":[0.9991208,0.0003483134,0.0001780313,0.0001514666,0.000165464,0.00003596395],"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":[0.0001220652,0.00005338678,0.001092061,0.0001492385,0.00006279285,0.000109343,0.0001448405,0.8172374,0.03749397,0.0151313,0.001101319,0.1273022],"study_design_scores_gemma":[0.000001916383,0.00001869731,0.0001535136,0.00000345942,0.000003813827,0.0000273728,0.00001059157,0.9947437,0.002978796,0.00161098,0.0004384417,0.000008635753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007188926,0.00006162211,0.9921968,0.00004768163,0.000009234993,0.000005702389,0.00001871086,0.0001605732,0.0003108293],"genre_scores_gemma":[0.4862913,0.0005249077,0.5091855,0.0001047196,0.00005588783,0.00006776973,0.0003210628,0.0001414143,0.003307565],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003278449,"threshold_uncertainty_score":0.006518722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05916406243374022,"score_gpt":0.2663235474821418,"score_spread":0.2071594850484016,"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."}}