{"id":"W2093426958","doi":"10.1587/transinf.e96.d.1602","title":"FPGA Design Framework Combined with Commercial VLSI CAD","year":2013,"lang":"en","type":"article","venue":"IEICE Transactions on Information and Systems","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Tokyo; Synopsys","keywords":"Field-programmable gate array; Computer science; Routing (electronic design automation); Bitstream; Embedded system; FPGA prototype; Very-large-scale integration; Code (set theory); Computer hardware; Computer architecture; Decoding methods; Set (abstract data type); Algorithm; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001165951,0.0001463654,0.0001602035,0.0001566345,0.0001438601,0.0002088345,0.00007268229,0.0001372504,0.00006856994],"category_scores_gemma":[0.000002762509,0.0001205211,0.00002491865,0.0001653711,0.00002636167,0.0009491944,6.821451e-7,0.000222659,0.0001744938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003866473,"about_ca_system_score_gemma":0.00001091209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001086896,"about_ca_topic_score_gemma":0.000004563633,"domain_scores_codex":[0.999309,0.00003285716,0.0002884234,0.00005927253,0.0001531976,0.0001572178],"domain_scores_gemma":[0.9995651,0.00008241346,0.00004016904,0.0001545968,0.00007222253,0.00008555524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003611042,0.0002368664,0.0002152695,0.001762565,0.0005664442,0.000004989544,0.01899144,0.4358372,0.0008524797,0.01007106,0.03380973,0.4972908],"study_design_scores_gemma":[0.003337816,0.00223789,0.003045477,0.001109042,0.0001477383,0.000176917,0.006222877,0.92515,0.01218171,0.0007802785,0.04364731,0.00196299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004144066,0.00003712091,0.9905694,0.00008101893,0.0002446061,0.0006895887,0.00001228653,0.0006628024,0.003559171],"genre_scores_gemma":[0.9966483,0.00006274162,0.002734552,0.0001331484,0.00002228751,0.0003104259,0.000007032497,0.00001450948,0.00006703968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9925042,"threshold_uncertainty_score":0.4914708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289755967590382,"score_gpt":0.2032000263192102,"score_spread":0.1903024666433064,"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."}}