{"id":"W2132958139","doi":"10.1109/icm.2003.237880","title":"Congestion driven placement for VLSI standard cell design","year":2003,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Router; Placement; Very-large-scale integration; Computer science; Interconnection; Routing (electronic design automation); Reduction (mathematics); Network routing; Integrated circuit layout; Chip; Parallel computing; Physical design; Electronic engineering; Embedded system; Integrated circuit; Circuit design; Engineering; Computer network; Mathematics; Telecommunications","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":[0.0002917834,0.0003473546,0.0001806885,0.0003855921,0.0002790712,0.0003812539,0.0004744559,0.0002260668,0.002477924],"category_scores_gemma":[0.000735239,0.0002079545,0.0001548317,0.000452428,0.0002641016,0.0004019167,0.000348627,0.0004097545,0.0005576496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004472159,"about_ca_system_score_gemma":0.0006454207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001722307,"about_ca_topic_score_gemma":0.003442817,"domain_scores_codex":[0.9998183,0.00004128176,0.000008316269,0.00001803759,0.00009428346,0.00001987666],"domain_scores_gemma":[0.9998245,0.00004914884,0.00002183628,0.0000324209,0.00006121282,0.00001093281],"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":[0.0002454621,0.00005694465,0.0006220564,0.0002020527,0.00003458703,0.0002958703,0.0001311809,0.4299138,0.09172416,0.06157831,0.007046373,0.4081492],"study_design_scores_gemma":[0.00006638396,0.0003740095,0.0004952076,0.00002442705,0.00002320594,0.0002352939,0.0000415683,0.9098873,0.03372648,0.03475748,0.02034121,0.00002745909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03399621,0.0009746964,0.959287,0.0001647573,0.0001288583,0.0001243988,0.00007901691,0.001198902,0.004046092],"genre_scores_gemma":[0.5110993,0.001172033,0.4799016,0.0001410102,0.00007473305,0.0001647195,0.0002652702,0.0001690113,0.007012211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002477924,"threshold_uncertainty_score":0.008289456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01860362526623188,"score_gpt":0.2198702142903698,"score_spread":0.2012665890241379,"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."}}