{"id":"W2041797988","doi":"10.1364/sppcom.2014.sw2c.3","title":"Digital Signal Processing for Coherent Optoelectronic Wavelength Conversion","year":2014,"lang":"en","type":"article","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Waveform; Optoelectronics; Modulation (music); Wavelength; Computer science; SIGNAL (programming language); Signal processing; Optics; Frequency conversion; Materials science; Electronic engineering; Digital signal processing; Physics; Telecommunications; Electrical engineering; Computer hardware; 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":[0.0001757008,0.0004390395,0.000214578,0.0004156613,0.0002762764,0.0007231419,0.0004816561,0.0003410579,0.005308032],"category_scores_gemma":[0.0009362971,0.0001314525,0.0001795184,0.0005512459,0.0002361162,0.0005792743,0.0002542858,0.0005700412,0.00101079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003278255,"about_ca_system_score_gemma":0.0003546743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002743654,"about_ca_topic_score_gemma":0.0005347446,"domain_scores_codex":[0.9997783,0.00003664841,0.000008987831,0.00002733755,0.0001234576,0.00002522467],"domain_scores_gemma":[0.9996992,0.0001268595,0.00001747002,0.00004761206,0.00009727562,0.00001154059],"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":[0.0003201427,0.0001685145,0.0007165094,0.0004625065,0.00003721023,0.0001956908,0.00007228418,0.01353465,0.5613309,0.0387912,0.001855532,0.3825149],"study_design_scores_gemma":[0.00008892198,0.0009016941,0.001550828,0.0001063468,0.00008578613,0.0008554239,0.00008885019,0.3607928,0.5898313,0.01168169,0.03397009,0.00004619225],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1166883,0.00309337,0.8459495,0.0005284885,0.0004881012,0.0002310282,0.0001547542,0.0008351518,0.03203119],"genre_scores_gemma":[0.6577602,0.002819652,0.3248022,0.0003130098,0.0001922083,0.0001772276,0.0003612357,0.00008402031,0.01349025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005308032,"threshold_uncertainty_score":0.01775712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006164211767214658,"score_gpt":0.1946725046684168,"score_spread":0.1885082929012021,"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."}}