{"id":"W2171697180","doi":"10.1109/glsv.1995.516024","title":"Optimizing wiring space in slicing floorplans","year":2002,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Floorplan; Slicing; Computer science; Heuristic; Space (punctuation); Integrated circuit layout; Mirroring; Branch and bound; Mathematical optimization; Topology (electrical circuits); Algorithm; Parallel computing; Mathematics; Integrated circuit; Embedded system; Combinatorics; Artificial intelligence","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":[0.00006346119,0.00008941682,0.00009987201,0.0001162978,0.00001765478,0.00002199275,0.00007539415,0.00005172028,0.0002647611],"category_scores_gemma":[0.000005158118,0.00009072469,0.00002168055,0.0001453257,0.000005839558,0.0001191385,0.00001268149,0.0001257336,0.00007013133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004150038,"about_ca_system_score_gemma":6.914913e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003319956,"about_ca_topic_score_gemma":0.0000333176,"domain_scores_codex":[0.9995285,0.000005893087,0.0001143172,0.00008911549,0.00005735826,0.0002048232],"domain_scores_gemma":[0.9998242,0.00001821885,0.000005775128,0.000114221,0.000004479914,0.00003315215],"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":[0.000005970632,0.0001845954,0.01356998,0.0004242877,0.00009642421,0.0003985708,0.01380754,0.4101241,0.3813447,0.009447767,0.05239726,0.1181988],"study_design_scores_gemma":[0.0002393202,0.00001973729,0.0004419187,0.0001029929,0.000004225554,0.0000162667,0.0001613285,0.8948407,0.1001012,0.0001336605,0.003590874,0.0003477841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1869147,0.0009808578,0.3321479,0.000150591,0.0001769766,0.0002185161,0.00000109531,0.003247603,0.4761618],"genre_scores_gemma":[0.975575,0.000138522,0.02365604,0.00003591181,0.00003620881,0.000008353439,4.281115e-7,0.00002340129,0.0005261737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7886603,"threshold_uncertainty_score":0.3699646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400861194722146,"score_gpt":0.1870251051480382,"score_spread":0.1730164932008167,"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."}}