{"id":"W3006619562","doi":"","title":"112-Gb/s PAM4 with Joint Pre- and Post-Equalization for Data Center Interconnects","year":2019,"lang":"en","type":"article","venue":"2019 Asia Communications and Photonics Conference (ACP)","topic":"Optical Network Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Equalization (audio); Joint (building); Bandwidth (computing); Computer science; Sensitivity (control systems); Blind equalization; Electronic engineering; Telecommunications; Engineering; 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":[0.0002430254,0.0006797189,0.0003301408,0.000371546,0.0003714014,0.0004084313,0.0005957829,0.0005313486,0.001725981],"category_scores_gemma":[0.0004103452,0.0002470097,0.0002595673,0.0004000676,0.0002840209,0.0005226951,0.0003702581,0.0004509905,0.0006237009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003688397,"about_ca_system_score_gemma":0.0006264771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008179492,"about_ca_topic_score_gemma":0.002347222,"domain_scores_codex":[0.9997682,0.00003357575,0.00001232276,0.00004198146,0.00009663965,0.00004732782],"domain_scores_gemma":[0.9997908,0.00003365127,0.00003587885,0.00003959076,0.00008390906,0.00001616243],"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":[0.0002957477,0.00009930066,0.001016746,0.0001075476,0.00002796462,0.00009684997,0.00004370615,0.005182197,0.928941,0.001468698,0.0005867968,0.06213338],"study_design_scores_gemma":[0.00003223066,0.00059136,0.0028571,0.0000115021,0.00004838773,0.0003975829,0.0000251033,0.08128737,0.9088931,0.0003706443,0.00544315,0.00004245332],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6163265,0.0008689311,0.3720049,0.0003375858,0.0001910661,0.0001348864,0.0001340446,0.002754707,0.007247307],"genre_scores_gemma":[0.8050308,0.0002143078,0.1893833,0.00007093464,0.00005235337,0.00005990129,0.0001426587,0.00005805002,0.004987668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001725981,"threshold_uncertainty_score":0.005773962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03957134220819303,"score_gpt":0.26297936490498,"score_spread":0.223408022696787,"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."}}