{"id":"W2170786135","doi":"10.1364/jocn.2.000701","title":"Analysis of Four-Wave Mixing Suppression in Fiber-Optic OFDM Transmission Systems With an Optical Phase Conjugation Module","year":2010,"lang":"en","type":"article","venue":"Journal of Optical Communications and Networking","topic":"Optical Network Technologies","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Four-wave mixing; Subcarrier; Orthogonal frequency-division multiplexing; Phase conjugation; Optics; Mixing (physics); Transmission (telecommunications); Optical fiber; Multiplexing; Phase (matter); Multi-mode optical fiber; Electronic engineering; Wavelength-division multiplexing; Optical power; Computer science; Physics; Nonlinear optics; Telecommunications; Engineering; Channel (broadcasting)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006916433,0.0001602779,0.000520985,0.000416326,0.00009438918,0.00007397157,0.0003775228,0.0002005977,0.00001040354],"category_scores_gemma":[0.00003744982,0.0001261567,0.00009074081,0.0008177128,0.000246467,0.0003035075,0.00008054145,0.000925174,2.767063e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003509047,"about_ca_system_score_gemma":0.00001972581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004318189,"about_ca_topic_score_gemma":0.00002740844,"domain_scores_codex":[0.9985446,0.0000760711,0.0007652932,0.0001259549,0.000244107,0.0002439229],"domain_scores_gemma":[0.998296,0.0006167286,0.0001783986,0.000603457,0.0001520061,0.0001534554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006331839,0.001385783,0.007716731,0.0002614652,0.001486102,0.00009949644,0.0007486196,0.3925856,0.04130452,0.02360606,0.00002679633,0.5301456],"study_design_scores_gemma":[0.000788807,0.0003767586,0.00179121,0.0003405104,0.0004217942,0.00007057481,0.0001375533,0.9950957,0.0002680087,0.0001588333,0.0003980806,0.0001521428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766486,0.001585473,0.02053076,0.0001732723,0.00009373236,0.0001435552,0.000002069582,0.00004936946,0.0007731542],"genre_scores_gemma":[0.8851388,0.0008714301,0.1138964,0.000003100836,0.00005529265,0.00000524579,0.000008198849,0.00001947071,0.000002147842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6025101,"threshold_uncertainty_score":0.5144522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03302613797361812,"score_gpt":0.2754599993922641,"score_spread":0.242433861418646,"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."}}