{"id":"W4389392180","doi":"10.1088/1742-6596/2649/1/012056","title":"Analysis of Verilog-based improvements to the memory transfer","year":2023,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Verilog; Computer architecture; Power consumption; Variety (cybernetics); Acceleration; Embedded system; Power (physics); Field-programmable gate array; Artificial intelligence","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":[0.003652784,0.0008103946,0.0003783747,0.001315182,0.0003709297,0.001351384,0.002246474,0.000789016,0.01155368],"category_scores_gemma":[0.02250776,0.0003483543,0.0006093447,0.0007527629,0.0009383784,0.002291263,0.0005864961,0.001107849,0.001153999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812748,"about_ca_system_score_gemma":0.002016861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002767009,"about_ca_topic_score_gemma":0.002865897,"domain_scores_codex":[0.9949032,0.00139255,0.0002343553,0.0004893939,0.002261632,0.0007188239],"domain_scores_gemma":[0.9726539,0.0198368,0.001351554,0.003128016,0.00287644,0.0001532891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004311586,0.0007778096,0.007004478,0.001865841,0.0001660902,0.000693685,0.0002235554,0.6243051,0.07043765,0.05309838,0.01319709,0.2239188],"study_design_scores_gemma":[0.0001057227,0.0006552505,0.000984517,0.00008637844,0.00007203127,0.000150222,0.00003561514,0.939863,0.04655609,0.006554789,0.004911565,0.00002473809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5270447,0.004656158,0.3917457,0.002175565,0.001002526,0.0004289779,0.002163842,0.03026401,0.04051846],"genre_scores_gemma":[0.9711298,0.0002732998,0.02603865,0.0001899536,0.00004699494,0.0000653876,0.000372556,0.000201311,0.001682002],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01155368,"threshold_uncertainty_score":0.03865087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040468532492566,"score_gpt":0.2721708525004474,"score_spread":0.2417661671755218,"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."}}