{"id":"W3013736034","doi":"10.1109/ccnc46108.2020.9045329","title":"Deep Learning Decoder for MIMO Communications with Impulsive Noise","year":2020,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; MIMO; Noise (video); Decoding methods; 3G MIMO; Electronic engineering; Telecommunications; Artificial intelligence; Speech recognition; Engineering; Beamforming","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":[],"consensus_categories":[],"category_scores_codex":[0.00005441717,0.0001043481,0.000126881,0.00003343178,0.000109964,0.00003511402,0.0005646177,0.0000500956,0.00004241649],"category_scores_gemma":[0.00003385625,0.00009943188,0.0000372472,0.0001500958,0.00004632273,0.0001254162,0.0001193003,0.0002270272,0.00002452608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002601087,"about_ca_system_score_gemma":0.000008447028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009128699,"about_ca_topic_score_gemma":0.00007545415,"domain_scores_codex":[0.999522,0.00002705375,0.0001517626,0.00009730218,0.00006534891,0.0001365024],"domain_scores_gemma":[0.9990428,0.0001710758,0.00002789957,0.0005877148,0.00009196506,0.00007853499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003159337,0.0005035473,0.01580761,0.001422479,0.001432277,0.000008102595,0.06449923,0.2305964,0.06696846,0.1792157,0.05307595,0.3861543],"study_design_scores_gemma":[0.0002970352,0.00007595182,0.0001704441,0.00001644122,0.00001706082,0.000002109391,0.0005667266,0.9019858,0.007025364,0.0002074107,0.08941319,0.0002224974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004841449,0.0006781733,0.9728002,0.003289483,0.000009964872,0.0004571636,0.000004175174,0.00215656,0.01576285],"genre_scores_gemma":[0.8102705,0.0003006499,0.1888105,0.0003295152,0.00001444024,0.0001684914,0.00003779144,0.00003912484,0.00002893923],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8054291,"threshold_uncertainty_score":0.4054714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193850686667621,"score_gpt":0.2564804380440819,"score_spread":0.2345419311774057,"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."}}