{"id":"W2097683623","doi":"10.1145/2554688.2554788","title":"Optimizing effective interconnect capacitance for FPGA power reduction","year":2014,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Capacitance; Reduction (mathematics); Interconnection; Field-programmable gate array; Power (physics); Materials science; Electronic engineering; Electrical engineering; Optoelectronics; Computer science; Embedded system; Engineering; Physics; Telecommunications; Electrode","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":[0.0001652379,0.00009735959,0.0001120226,0.00005548524,0.00003202602,0.00002033845,0.00006208624,0.00006199385,0.00003005111],"category_scores_gemma":[0.00003702971,0.00008989932,0.00005277852,0.00005395492,0.00001376695,0.0001321646,0.000002835693,0.00007101436,0.00001330063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004995115,"about_ca_system_score_gemma":0.000001375901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003606154,"about_ca_topic_score_gemma":0.000001715296,"domain_scores_codex":[0.9995865,0.00001455824,0.00009544908,0.0001176543,0.00003764849,0.0001482077],"domain_scores_gemma":[0.999734,0.00007054814,0.00001136893,0.0001242963,0.00003060363,0.00002917207],"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":[0.00002744372,0.00002178622,0.000007540451,0.0001286902,0.00007545824,5.030278e-7,0.001446245,0.00336314,0.8148024,0.01232519,0.01676524,0.1510363],"study_design_scores_gemma":[0.0001989104,0.0001809333,0.00002066251,0.00004187884,0.000008842981,0.000008180928,0.00009858197,0.02188895,0.9683774,0.003101735,0.005873608,0.0002003143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01590688,0.00007999012,0.9537829,0.00002290251,0.0003671857,0.0003587332,0.000001546463,0.001007424,0.02847244],"genre_scores_gemma":[0.960762,0.000007868735,0.03876595,0.00002482573,0.00009080894,0.0001657861,0.000001905439,0.00002704081,0.0001538357],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9448551,"threshold_uncertainty_score":0.3665988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006285665850792426,"score_gpt":0.2094604974994567,"score_spread":0.2031748316486642,"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."}}