{"id":"W2150336620","doi":"10.1287/ijoc.1040.0127","title":"Integer Linear Programming Models for Global Routing","year":2006,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Integer programming; Branch and price; Branch and cut; Linear programming; Mathematical optimization; Integer (computer science); Mathematics; Linear programming relaxation; Routing (electronic design automation); Branch and bound; Computer science; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004590796,0.0001943182,0.0002061231,0.00008922534,0.0002158551,0.0002083182,0.0001966238,0.0001028716,0.000002198294],"category_scores_gemma":[0.00002675542,0.000161401,0.0001561982,0.0001646154,0.00001544434,0.0003552077,0.00002920304,0.000351863,0.000006170698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002061607,"about_ca_system_score_gemma":0.00002364845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006867514,"about_ca_topic_score_gemma":0.000001553374,"domain_scores_codex":[0.9986924,0.000006440363,0.0005409757,0.00009942266,0.000196554,0.0004642221],"domain_scores_gemma":[0.9995256,0.00006382273,0.0001208949,0.0001002813,0.0001098761,0.00007952499],"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":[0.00001196536,0.00001938109,0.0003042528,0.00003789409,0.00002926758,0.00001202649,0.0001031899,0.6460422,0.00008406703,0.01062815,0.000978207,0.3417495],"study_design_scores_gemma":[0.0003550439,0.0001189233,0.00006145889,0.0002061192,0.000009081326,0.0001717715,0.0000469673,0.9832591,0.001046101,0.008325826,0.006156056,0.0002435746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03248442,0.00008991202,0.9576182,0.0000231828,0.0003827553,0.0002071172,0.000002567786,0.0006681498,0.008523691],"genre_scores_gemma":[0.9129832,0.000004625461,0.08602285,0.00007781859,0.0008511646,0.000004213424,0.000004591978,0.00002878332,0.00002272861],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8804988,"threshold_uncertainty_score":0.6581742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01661284083326245,"score_gpt":0.2549549355216916,"score_spread":0.2383420946884292,"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."}}