{"id":"W4241047385","doi":"10.1109/lsp.2017.2755418","title":"IEEE Signal Processing Society Editorial Board","year":2017,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidad Rey Juan Carlos; Universidade Estadual de Campinas; Yonsei University; Institut national de recherche en informatique et en automatique (INRIA); McGill University; RWTH Aachen University; Johns Hopkins University; École Polytechnique Fédérale de Lausanne; University of Maryland, Baltimore County","keywords":"Signal processing; Computer science; Multidimensional signal processing; Telecommunications; Digital signal processing; Computer hardware","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009359531,0.0004105009,0.0004050202,0.0001173889,0.002314663,0.001574811,0.002651293,0.0003791957,0.000006513138],"category_scores_gemma":[0.00002775958,0.0003878826,0.0002259769,0.0002131467,0.0004901092,0.002010626,0.00006853275,0.0007438926,0.00006789522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001472834,"about_ca_system_score_gemma":0.0002771512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004213463,"about_ca_topic_score_gemma":0.000003841787,"domain_scores_codex":[0.9965147,0.00007974905,0.0004803207,0.0009373772,0.001148957,0.0008388305],"domain_scores_gemma":[0.9979903,0.00004828503,0.0006995738,0.0008220217,0.0002754108,0.0001643847],"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":[0.00002806061,0.00007253552,0.0007031193,0.0001983252,0.00005138652,0.00004168662,0.0009835638,0.0002216596,0.7828701,0.00002976687,0.1306683,0.08413154],"study_design_scores_gemma":[0.00474763,0.0003628789,0.001495251,0.001926878,0.000190584,0.0001595674,0.0002702414,0.103172,0.818539,0.001644165,0.06431174,0.003180072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07499459,0.000275815,0.8862033,0.008992706,0.02704585,0.0004533987,0.000003039406,0.001313646,0.0007175927],"genre_scores_gemma":[0.9690012,0.000002474651,0.007054638,0.001993995,0.02174855,0.00004034456,0.00000104014,0.00003903626,0.0001187071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8940066,"threshold_uncertainty_score":0.9998573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105019369148025,"score_gpt":0.2616335269155358,"score_spread":0.2305833332240555,"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."}}