{"id":"W1603560063","doi":"10.1002/9780470630976.ch21","title":"Integrated Circuits for Dispersion Compensation in Optical Communication Links","year":2010,"lang":"en","type":"other","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Infinite impulse response; Electronic engineering; Compensation methods; Impulse response; Compensation (psychology); Optical communication; Linear filter; Computer science; Equalization (audio); Dispersion (optics); Finite impulse response; Maximum likelihood sequence estimation; Intersymbol interference; Optical fiber; Filter (signal processing); Engineering; Optics; Telecommunications; Digital filter; Mathematics; Estimation theory; Physics; Algorithm; Channel (broadcasting)","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":[0.0001939905,0.0006761531,0.000325308,0.0006518203,0.000377393,0.001071613,0.0007546951,0.0008662653,0.0150716],"category_scores_gemma":[0.0004874604,0.0002570074,0.0002824447,0.0007957235,0.0002844477,0.0009490697,0.0003757589,0.000789723,0.005665732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000642586,"about_ca_system_score_gemma":0.000332866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000434947,"about_ca_topic_score_gemma":0.0008648501,"domain_scores_codex":[0.999605,0.00003529045,0.00001397987,0.00005651992,0.0002662635,0.00002308017],"domain_scores_gemma":[0.9998702,0.00003511856,0.00002028651,0.00001826631,0.00004953417,0.000006561183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007986009,0.0001179808,0.0004028773,0.000574369,0.00004365439,0.0002287403,0.000152107,0.004810002,0.1878567,0.09340563,0.02812693,0.6842011],"study_design_scores_gemma":[0.00005271638,0.0004230377,0.001471897,0.0003616153,0.0001207878,0.001771029,0.00007036882,0.04110296,0.118569,0.01911309,0.8168846,0.00005886492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.021138,0.04154382,0.655522,0.001500573,0.001875519,0.0004217972,0.0004061947,0.004016924,0.2735751],"genre_scores_gemma":[0.1965158,0.02800893,0.4719859,0.001284586,0.001001195,0.0003723036,0.000754705,0.0003622337,0.2997144],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0150716,"threshold_uncertainty_score":0.05041951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420021696136495,"score_gpt":0.2315960824282014,"score_spread":0.2173958654668365,"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."}}