{"id":"W3196902411","doi":"10.1109/blackseacom52164.2021.9527735","title":"Geometric Constellation Shaping Using Initialized Autoencoders","year":2021,"lang":"en","type":"article","venue":"","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); Université Laval","funders":"","keywords":"QAM; Initialization; Quadrature amplitude modulation; Computer science; Constellation; Algorithm; Artificial intelligence; Bit error rate; Decoding methods; Physics","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":[0.0007019045,0.0007652817,0.0005338648,0.000362352,0.0002489286,0.000502129,0.0006339324,0.0007592729,0.0009938049],"category_scores_gemma":[0.00278326,0.0003718168,0.0003957989,0.0002828497,0.0009088485,0.0008236297,0.0007239836,0.001083257,0.0003628039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000559178,"about_ca_system_score_gemma":0.0006011277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00176558,"about_ca_topic_score_gemma":0.001990756,"domain_scores_codex":[0.9996933,0.00009461953,0.00001447898,0.0000796524,0.00007511286,0.00004302022],"domain_scores_gemma":[0.9989989,0.0005095666,0.0001156955,0.0001351788,0.0002099896,0.00003069365],"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":[0.00008237106,0.00002705286,0.0004223293,0.0000284862,0.00002323606,0.00005339208,0.0000510889,0.9286675,0.009207258,0.006822396,0.0005818597,0.05403307],"study_design_scores_gemma":[0.00000344887,0.00001807444,0.00005894331,0.000004119333,0.000002312394,0.00001053119,0.000003064447,0.9955042,0.002581184,0.001651708,0.0001586473,0.000003807959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04115103,0.0001392848,0.9559816,0.0001452093,0.00004498551,0.00002409966,0.00002939939,0.0005542251,0.001930265],"genre_scores_gemma":[0.7840724,0.0001365452,0.2128963,0.0001774572,0.00003747607,0.00005455705,0.000135171,0.00008102322,0.002409103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00176558,"threshold_uncertainty_score":0.004057169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1347465924859403,"score_gpt":0.3103993443681582,"score_spread":0.175652751882218,"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."}}