{"id":"W4231804678","doi":"10.1504/ijcaet.2021.115355","title":"Latency-optimised 3D multi-FPGA system with serial optical interface","year":2021,"lang":"en","type":"article","venue":"International Journal of Computer Aided Engineering and Technology","topic":"Semiconductor Lasers and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Latency (audio); Field-programmable gate array; Benchmark (surveying); Embedded system; Routing (electronic design automation); Three-dimensional integrated circuit; Reduction (mathematics); System on a chip; Interface (matter); Electronic engineering; Computer hardware; Chip; Parallel computing; Engineering; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.00006141902,0.0001447619,0.0002458637,0.0002368974,0.000013138,0.00006766302,0.000230087,0.0001217116,0.000009371505],"category_scores_gemma":[0.00002048848,0.0001227993,0.00003926417,0.0001390327,0.00003502476,0.0001159721,0.00006596657,0.0003104968,0.000003351867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000636423,"about_ca_system_score_gemma":0.00002354118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.073676e-7,"about_ca_topic_score_gemma":7.442454e-7,"domain_scores_codex":[0.9992505,0.000005558983,0.0003099925,0.0001171968,0.0001590324,0.0001576659],"domain_scores_gemma":[0.9994353,0.00004854252,0.00004740344,0.00009447269,0.0002974071,0.00007689679],"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":[0.00006158275,0.00007303717,0.0003893777,0.0001574073,0.001064128,0.001811976,0.0001228133,0.9172003,0.05917751,0.00349249,0.0001583917,0.01629096],"study_design_scores_gemma":[0.001835502,0.0001618798,0.0003269092,0.0005432179,0.00004282095,0.004469583,0.00009773337,0.924027,0.06638994,0.00002606038,0.001818676,0.0002607174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5761037,0.0006658023,0.4210419,0.0002386613,0.00164761,0.00002856141,0.000003344288,0.0002117953,0.00005854853],"genre_scores_gemma":[0.8930961,0.00006246216,0.1065481,0.00001282055,0.0002486295,0.000001496032,0.000001563207,0.0000212417,0.000007573223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3169924,"threshold_uncertainty_score":0.5007612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005362390747558589,"score_gpt":0.1992604548356665,"score_spread":0.1938980640881079,"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."}}