{"id":"W2532917096","doi":"10.1109/icm.2009.5418618","title":"A novel framework of Optimizing modular computing architecture for multi objective VLSI designs","year":2009,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Very-large-scale integration; Computer science; Application-specific integrated circuit; Modular design; Computer architecture; Electronic design automation; Embedded system; Floorplan; Computer engineering; Distributed computing","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":[0.000615148,0.0002282971,0.0003860338,0.0002074372,0.0001180956,0.00006335234,0.001019569,0.0001872357,0.000001194734],"category_scores_gemma":[0.0002124021,0.0002036282,0.0001710402,0.0004184744,0.00003744102,0.0002145355,0.000127504,0.00024619,0.000001263154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006256473,"about_ca_system_score_gemma":0.00006220216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003110292,"about_ca_topic_score_gemma":0.000002089231,"domain_scores_codex":[0.9983112,0.00008018137,0.0004350503,0.0005218622,0.0002577187,0.0003939617],"domain_scores_gemma":[0.9983318,0.0004321676,0.0002374504,0.0006827348,0.0002314604,0.00008433624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003761851,0.0004953917,0.00009999854,0.0001289911,0.0001035142,0.000009080388,0.01136927,0.0367251,0.4726069,0.4134876,0.000276582,0.06465995],"study_design_scores_gemma":[0.0004182389,0.0004505013,0.0002619661,0.0002601829,0.000008686354,0.0000344461,0.00009101365,0.7554224,0.2168164,0.02587871,0.00002852379,0.0003288915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008537316,0.00009290488,0.9967048,0.0001641421,0.00009918473,0.0009380943,0.00000319858,0.0006461479,0.0004977617],"genre_scores_gemma":[0.423117,5.354324e-7,0.5765585,0.0002360252,0.00003879277,0.00001112436,4.696288e-7,0.000009619317,0.00002789128],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7186973,"threshold_uncertainty_score":0.8303716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05469676730474518,"score_gpt":0.3170555504620938,"score_spread":0.2623587831573486,"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."}}