{"id":"W2162180547","doi":"10.1109/iscas.2005.1466066","title":"Fast Integer Linear Programming Based Models for VLSI Global Routing","year":2005,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Router; Integer programming; Computer science; Routing (electronic design automation); Very-large-scale integration; Mathematical optimization; Pruning; Tree (set theory); Minification; Linear programming; Global optimization; Parallel computing; Algorithm; Mathematics; Computer network; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008879915,0.001162668,0.000681015,0.0004275501,0.0003591995,0.001244223,0.001107129,0.001080362,0.006413601],"category_scores_gemma":[0.002027033,0.0005633498,0.0008694308,0.001141274,0.0006146582,0.001349439,0.0006207526,0.002134951,0.001309073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009057835,"about_ca_system_score_gemma":0.0009285928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002792719,"about_ca_topic_score_gemma":0.003914543,"domain_scores_codex":[0.9995669,0.0001703724,0.00001474248,0.00004756863,0.0001492337,0.00005123226],"domain_scores_gemma":[0.9991838,0.000618895,0.00005859831,0.00003840963,0.00008538096,0.00001483069],"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":[0.00001749895,0.00001887584,0.00005715485,0.00004339636,0.000008310698,0.00003280218,0.00002510303,0.9355156,0.000382016,0.05081265,0.001390854,0.0116957],"study_design_scores_gemma":[0.000005141073,0.000009129744,0.00001026249,0.000004132875,0.000002218084,0.000006414016,0.000004695669,0.9850117,0.0001070569,0.01358032,0.001256551,0.000002285091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002124443,0.0004314314,0.9902797,0.000218756,0.00003227301,0.00003902729,0.0001142872,0.0002019596,0.006558144],"genre_scores_gemma":[0.2823774,0.003211831,0.6873963,0.0003284424,0.000166011,0.001134928,0.0007456724,0.0002945436,0.02434492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006413601,"threshold_uncertainty_score":0.02145565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01884667185012392,"score_gpt":0.2509818510131497,"score_spread":0.2321351791630258,"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."}}