{"id":"W2782281681","doi":"10.1109/tcad.2018.2789728","title":"Density-Uniformity-Aware Analog Layout Retargeting","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Research and Development Corporation of Newfoundland and Labrador; Canada Foundation for Innovation","keywords":"Retargeting; Computer science; Process (computing); Electronic engineering; Capacitance; Set (abstract data type); Integrated circuit layout; Place and route; Integrated circuit; Electrical engineering; Engineering; Artificial intelligence; Routing (electronic design automation)","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":[0.0001579233,0.0004137681,0.0001981678,0.0003224211,0.000212253,0.0003216202,0.0007048915,0.0001614496,0.001051481],"category_scores_gemma":[0.0008186299,0.000176069,0.0001280487,0.0002637219,0.0002852826,0.0004325158,0.0005862818,0.0001995527,0.0002596522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318097,"about_ca_system_score_gemma":0.0002080108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004533201,"about_ca_topic_score_gemma":0.001191966,"domain_scores_codex":[0.9997427,0.00003261065,0.00001491436,0.0000812306,0.00009360023,0.00003498553],"domain_scores_gemma":[0.999363,0.0001098331,0.0001736456,0.0002264709,0.0001004203,0.00002656891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001706087,0.00006950493,0.001711404,0.0001439555,0.00002873854,0.00016783,0.0001979915,0.0170962,0.8866086,0.002540165,0.0009033941,0.09036164],"study_design_scores_gemma":[0.00003661169,0.0004992146,0.005118314,0.00001182223,0.00006069723,0.0006276716,0.00007651081,0.1003474,0.8832803,0.001198587,0.008710345,0.00003263331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5168272,0.0009625619,0.4687229,0.0001962554,0.0001207526,0.0001029321,0.0001590619,0.004569547,0.008338864],"genre_scores_gemma":[0.9529008,0.0001297525,0.04472448,0.00008063351,0.00002048336,0.00001893677,0.00006707716,0.0001204838,0.00193739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001051481,"threshold_uncertainty_score":0.003517568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524425396922366,"score_gpt":0.2188628959097165,"score_spread":0.1936186419404928,"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."}}