{"id":"W2784203650","doi":"10.1109/piers.2017.8261781","title":"Development and study of demodulators for frequency-hopping spread spectrum signals","year":2017,"lang":"en","type":"article","venue":"2017 Progress In Electromagnetics Research Symposium - Spring (PIERS)","topic":"Advanced Signal Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Federation for the Humanities and Social Sciences","keywords":"Demodulation; Frequency-hopping spread spectrum; Computer science; Signal-to-noise ratio (imaging); SIGNAL (programming language); Electronic engineering; Noise (video); MATLAB; Direct-sequence spread spectrum; Spread spectrum; Frequency modulation; Telecommunications; Channel (broadcasting); Engineering; Artificial intelligence; Radio frequency","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001856648,0.0003377572,0.0004830381,0.000602642,0.0006747736,0.0003116455,0.001117046,0.0001839203,0.000003177764],"category_scores_gemma":[0.00020274,0.0003645782,0.00004461091,0.0002191011,0.0004303883,0.0003903852,0.0003645474,0.0007132007,0.000001637599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000300531,"about_ca_system_score_gemma":0.0001394727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000051108,"about_ca_topic_score_gemma":0.0001942062,"domain_scores_codex":[0.9968292,0.00008669173,0.000613004,0.0005846516,0.0007133615,0.00117306],"domain_scores_gemma":[0.9983484,0.0001768412,0.0001846982,0.00089632,0.0002150243,0.0001786973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003353351,0.001324708,0.180818,0.003140054,0.0004619815,0.0002018258,0.007163772,0.002372073,0.7131824,0.004448757,0.0001645621,0.0863865],"study_design_scores_gemma":[0.004722616,0.005767256,0.06272452,0.002000313,0.00008125418,0.00002672783,0.0008798604,0.0615775,0.8426903,0.01628406,0.001205139,0.00204046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913663,0.002928925,0.002672916,0.00010956,0.00009971345,0.001715583,0.000003269321,0.000235766,0.0008679712],"genre_scores_gemma":[0.944929,0.0002877655,0.05410802,0.000001907441,0.00007062383,0.0004707995,0.000001640533,0.00009562467,0.0000346149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1295079,"threshold_uncertainty_score":0.9998806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05233094504893398,"score_gpt":0.3663913830568004,"score_spread":0.3140604380078664,"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."}}