{"id":"W4413278528","doi":"10.1109/icfpt64416.2024.11113427","title":"A Regression-Based Approach Towards Estimating the Area, Delay and Leakage Power of Synthesizable FPGA Tiles","year":2024,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Field-programmable gate array; Leakage (economics); Computer science; Leakage power; Regression; Regression analysis; Embedded system; Power (physics); Parallel computing; Computer architecture; Statistics; Power consumption; Mathematics; Machine learning","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":[0.0004546142,0.0009273965,0.0006211151,0.0006893901,0.0001638458,0.0005286136,0.0006620554,0.0004985437,0.001312685],"category_scores_gemma":[0.001970045,0.0005540755,0.0007715028,0.0005974931,0.0002929125,0.0006127289,0.0003202284,0.0007333447,0.0005727259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004903371,"about_ca_system_score_gemma":0.000627293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00275416,"about_ca_topic_score_gemma":0.003961049,"domain_scores_codex":[0.9995804,0.00009051873,0.00001772351,0.0001374758,0.0001396596,0.00003411269],"domain_scores_gemma":[0.9992471,0.0003987003,0.0001282864,0.00009863045,0.0001142652,0.00001305081],"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":[0.00002430527,0.00002272173,0.0006814374,0.00004864747,0.00003466659,0.00003701448,0.00001745255,0.9348029,0.02361282,0.001102582,0.0001370996,0.03947832],"study_design_scores_gemma":[0.000001838275,0.0000312862,0.0002569027,0.000003370458,0.00000952426,0.00002162311,0.000003361521,0.9940176,0.004907223,0.0004212239,0.000322011,0.000004064308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02057557,0.0001419303,0.9776216,0.00002752836,0.000005501892,0.00002383524,0.00008785935,0.0006797622,0.0008364723],"genre_scores_gemma":[0.5587476,0.0003915096,0.4366789,0.00006152591,0.00002677453,0.0001724815,0.0004718503,0.0003159533,0.003133368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00275416,"threshold_uncertainty_score":0.005476236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02618053875249945,"score_gpt":0.2493549992031996,"score_spread":0.2231744604507001,"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."}}