{"id":"W1719300925","doi":"10.1007/3-540-46117-5_33","title":"A Flexible Power Model for FPGAs","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":178,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Field-programmable gate array; Computer science; CAD; Computer architecture; Design flow; Embedded system; Variety (cybernetics); Power (physics); Power optimization; Reconfigurable computing; Power analysis; Engineering; Engineering drawing; Artificial intelligence; Power consumption; Algorithm","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":[0.0001952349,0.0006704445,0.000408779,0.0003458706,0.0003239935,0.000984746,0.001515934,0.0006177971,0.008839677],"category_scores_gemma":[0.0007661066,0.0003344105,0.0005879432,0.0005368512,0.0004186075,0.00170802,0.0005801064,0.001117547,0.001990146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003883773,"about_ca_system_score_gemma":0.0002603306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009202887,"about_ca_topic_score_gemma":0.001367881,"domain_scores_codex":[0.9998376,0.00003218489,0.000008798876,0.00002775744,0.00006699966,0.00002656052],"domain_scores_gemma":[0.9998499,0.0000516549,0.000009109533,0.00004804872,0.00003297796,0.000008326151],"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":[0.00008024905,0.00003029663,0.0001542032,0.0001367156,0.00002008941,0.0001723399,0.00007721053,0.6332913,0.006952747,0.2863391,0.004309042,0.06843656],"study_design_scores_gemma":[0.00001535519,0.00003346575,0.00005932145,0.000015835,0.00001049135,0.00009399656,0.00001402553,0.906172,0.001429239,0.07975636,0.01239223,0.000007699558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008963725,0.0007386174,0.9562639,0.0003012504,0.0001125143,0.00004124882,0.0002259817,0.0006229673,0.03272985],"genre_scores_gemma":[0.6983547,0.002055503,0.2373842,0.0003861669,0.0001553516,0.0002397884,0.0005127529,0.00079356,0.06011802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008839677,"threshold_uncertainty_score":0.02957165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02018095815751529,"score_gpt":0.2200088772479058,"score_spread":0.1998279190903905,"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."}}