{"id":"W4205723155","doi":"10.3390/s22010333","title":"Design of a SIMO Deep Learning-Based Chaos Shift Keying (DLCSK) Communication System","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Demodulation; Keying; Computer science; Synchronization (alternating current); Channel (broadcasting); Electronic engineering; Bit error rate; Chaotic; Communications system; Algorithm; Real-time computing; Telecommunications; Artificial intelligence; Engineering","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":[0.0002659307,0.0004422553,0.000515671,0.0002140038,0.0004770235,0.0005394171,0.001054069,0.0006853522,0.00235162],"category_scores_gemma":[0.0002672001,0.0002953925,0.00033268,0.00019948,0.0004125703,0.000618663,0.0007120703,0.0006316018,0.0008459255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007174996,"about_ca_system_score_gemma":0.0008133972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001898413,"about_ca_topic_score_gemma":0.002528134,"domain_scores_codex":[0.9997141,0.00003695877,0.00002087784,0.00008764764,0.00009830197,0.00004212231],"domain_scores_gemma":[0.9998624,0.00001911726,0.00002118759,0.00001314525,0.00006541616,0.00001859454],"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":[0.0006190818,0.000372516,0.004466686,0.0006298109,0.0001959417,0.0008654171,0.0003295597,0.3725141,0.2192052,0.03697632,0.009231634,0.3545938],"study_design_scores_gemma":[0.00002723403,0.0001859209,0.0003096121,0.00001664704,0.00002515433,0.0001258263,0.00001401744,0.9768654,0.01611493,0.001476498,0.004818373,0.00002044074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03115794,0.0004342833,0.9547395,0.0005416079,0.000163443,0.0001828998,0.0001168326,0.001293602,0.01136995],"genre_scores_gemma":[0.8233357,0.0002595717,0.1679164,0.0004515481,0.00006283266,0.0002609012,0.0001456342,0.00004502952,0.007522395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00235162,"threshold_uncertainty_score":0.007866919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111349889641551,"score_gpt":0.2236101316093062,"score_spread":0.2124966327128907,"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."}}