{"id":"W1900671596","doi":"","title":"Linear cross talk in wave-mixing optical cross connects","year":2003,"lang":"en","type":"article","venue":"Journal of Optical Networking","topic":"Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Mixing (physics); Converters; Electronic engineering; Transmission (telecommunications); Computer science; Point (geometry); Scalability; Four-wave mixing; Topology (electrical circuits); Telecommunications; Physics; Engineering; Electrical engineering; Power (physics); Optics; Mathematics; Nonlinear optics; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001226339,0.0003399212,0.000669734,0.0002163752,0.00009294807,0.0002328869,0.0003773843,0.000451885,0.00004360145],"category_scores_gemma":[0.0009295435,0.0003108463,0.000225902,0.0005312208,0.0003169089,0.0003891985,0.0001011859,0.00166401,0.00001413385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000225613,"about_ca_system_score_gemma":0.00004244887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.511985e-7,"about_ca_topic_score_gemma":0.000005183853,"domain_scores_codex":[0.9969776,0.00004265398,0.001218524,0.0002501244,0.0004836349,0.00102741],"domain_scores_gemma":[0.9983326,0.000818212,0.0001364339,0.0002912745,0.0001360851,0.000285362],"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":[0.0001132769,0.0002075648,0.01658939,0.0001032315,0.0001515909,0.001834885,0.00008026657,0.917382,0.00346423,0.04730051,0.0001658843,0.01260719],"study_design_scores_gemma":[0.00637086,0.0008684124,0.01684147,0.001789614,0.0001320962,0.003980187,0.0002325451,0.9156711,0.01862598,0.01081907,0.02263631,0.00203232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9554428,0.00151617,0.02745682,0.0001058614,0.002113708,0.0001440542,8.674701e-7,0.0002349189,0.01298473],"genre_scores_gemma":[0.9129559,0.0002164223,0.08583128,0.00005253735,0.000841256,0.000003367116,5.579076e-7,0.00007109793,0.0000275786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05837446,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02239750209888556,"score_gpt":0.2697063905409905,"score_spread":0.2473088884421049,"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."}}