{"id":"W1972437065","doi":"10.1109/tvlsi.2012.2202326","title":"Combined Architecture/Algorithm Approach to Fast FPGA Routing","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Field-programmable gate array; Routing (electronic design automation); Logic block; Router; Multipath routing; Parallel computing; Static routing; Algorithm; Embedded system; Computer network; Routing protocol","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005383338,0.0004203089,0.0004297601,0.000427694,0.0002789535,0.0001597102,0.0002489193,0.000284882,0.00003508166],"category_scores_gemma":[0.000005844396,0.0003897337,0.0002063858,0.0005554524,0.00002843532,0.0004178105,0.00000212665,0.0006186671,0.0001889849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002882482,"about_ca_system_score_gemma":0.00001970166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006701957,"about_ca_topic_score_gemma":0.00002284739,"domain_scores_codex":[0.9978293,0.0001459291,0.0005839164,0.0003383825,0.0004108078,0.0006916532],"domain_scores_gemma":[0.9989887,0.0000747755,0.00006409175,0.0004703915,0.0001000302,0.000301947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001784465,0.002984065,0.0001479551,0.0006893558,0.0006825518,0.000009010251,0.022783,0.4210949,0.07384565,0.001635416,0.01040674,0.4655429],"study_design_scores_gemma":[0.001271761,0.0004032169,0.000165466,0.0005496844,0.0001435646,0.0001275075,0.0041975,0.7166884,0.2658886,0.00005014693,0.00894018,0.001573994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005039765,0.0001224956,0.9838908,0.00002320744,0.002554752,0.00095647,0.0001792244,0.001581958,0.005651378],"genre_scores_gemma":[0.9868439,0.00001773737,0.01124023,0.00006596684,0.0003553138,0.0005359186,0.00003979156,0.0001009433,0.0008002284],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9818041,"threshold_uncertainty_score":0.9998555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192940404766944,"score_gpt":0.2161783869897539,"score_spread":0.2042489829420845,"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."}}