{"id":"W4383960635","doi":"10.1109/tvt.2023.3294237","title":"Asynchronous Denoise and Forward Two-Way Relay Using ECPM","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Relay; Asynchronous communication; Decoding methods; Computer science; Synchronization (alternating current); Relay channel; Bit error rate; Signal-to-noise ratio (imaging); Ergodic theory; Chaotic; Noise (video); Algorithm; Control theory (sociology); Electronic engineering; Real-time computing; Channel (broadcasting); Mathematics; Telecommunications; Engineering; Artificial intelligence","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":[0.0005228718,0.0009073162,0.0006796427,0.0004097186,0.0004827809,0.0006763354,0.0007494247,0.0006473718,0.000917898],"category_scores_gemma":[0.001191837,0.0001882138,0.0004495963,0.0005107158,0.0005239145,0.001001506,0.0006965877,0.0005225093,0.0003583116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004544953,"about_ca_system_score_gemma":0.0004360055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176726,"about_ca_topic_score_gemma":0.001289002,"domain_scores_codex":[0.9994968,0.000171397,0.0000296183,0.0001196986,0.000140304,0.00004207719],"domain_scores_gemma":[0.9996258,0.0001500911,0.00005508498,0.00007511874,0.00007682485,0.00001705753],"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":[0.0008097708,0.0001654129,0.001609631,0.0004376935,0.0001795088,0.001200109,0.0008485953,0.4079229,0.1845842,0.08279499,0.003003867,0.3164432],"study_design_scores_gemma":[0.00005668536,0.0002770754,0.0002461536,0.00002269399,0.00006579775,0.0007390358,0.00005171499,0.9417296,0.04436412,0.008069959,0.004328945,0.00004817136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02669637,0.0004286173,0.968527,0.0001147762,0.0000595688,0.00006129436,0.00004320059,0.0003977338,0.003671452],"genre_scores_gemma":[0.7702701,0.0004708545,0.2255401,0.00008611687,0.00004918316,0.0001001783,0.00005933505,0.00002546901,0.00339867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001176726,"threshold_uncertainty_score":0.003297627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322672300944301,"score_gpt":0.2517471729224833,"score_spread":0.2385204499130403,"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."}}