{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003828474,0.0009619174,0.0004246384,0.0009660191,0.0002445987,0.0007276776,0.00159225,0.0004555795,0.02958664],"category_scores_gemma":[0.00061004,0.0003808554,0.0006520622,0.0005977437,0.0001735403,0.0004766972,0.0003743826,0.0007003876,0.009722051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005741516,"about_ca_system_score_gemma":0.0009814402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002625931,"about_ca_topic_score_gemma":0.003119673,"domain_scores_codex":[0.9996507,0.00004417465,0.00002325143,0.0000429898,0.0001879511,0.00005090823],"domain_scores_gemma":[0.9997525,0.00004943736,0.0000181908,0.00004676927,0.000118176,0.00001487326],"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":[0.0003267594,0.0001499323,0.001181114,0.001216494,0.0001130535,0.0008802805,0.0001920077,0.1255126,0.07685255,0.08593578,0.09058653,0.6170529],"study_design_scores_gemma":[0.0002802757,0.0004099965,0.00107402,0.0001382067,0.00008231567,0.001537697,0.00003854487,0.3425773,0.06847996,0.01196254,0.5733172,0.0001018658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004364162,0.0004877942,0.9334045,0.00009344108,0.00009519321,0.0003081461,0.0009903125,0.02211859,0.03813791],"genre_scores_gemma":[0.07268306,0.000591777,0.8959968,0.0002061255,0.00005279085,0.0006983461,0.004053529,0.002412912,0.02330471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02958664,"threshold_uncertainty_score":0.09897721,"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."}}