{"id":"W2132665983","doi":"10.1109/iccd.2006.4380823","title":"RTL Scan Design for Skewed-Load At-Speed Test under Power Constraints","year":2006,"lang":"en","type":"article","venue":"Proceedings, IEEE International Conference on Computer Design/Proceedings - IEEE International Conference on Computer Design","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Netlist; Automatic test pattern generation; Register-transfer level; Computer science; Partition (number theory); Scan chain; Fault coverage; Circuit extraction; Test compression; Power (physics); Test vector; Design for testing; Logic gate; Logic synthesis; Embedded system; Reliability engineering; Algorithm; Integrated circuit; Electronic circuit; Engineering; Equivalent circuit; Mathematics; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003501946,0.0004566375,0.0003219859,0.0007631672,0.0003184774,0.0005082965,0.0009998764,0.0003828167,0.005692805],"category_scores_gemma":[0.001222552,0.0002730575,0.0003528541,0.0005474662,0.0004757026,0.0008126282,0.0004542625,0.0004504268,0.000948949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005601862,"about_ca_system_score_gemma":0.0006760519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001123842,"about_ca_topic_score_gemma":0.002524401,"domain_scores_codex":[0.9993564,0.000172915,0.00003030486,0.00009020772,0.0002811633,0.0000690507],"domain_scores_gemma":[0.999009,0.0003843807,0.0001673957,0.0001916719,0.0002189893,0.00002848354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005399938,0.0001607785,0.003338157,0.0005252801,0.000113884,0.001024921,0.0004463397,0.1752133,0.2879242,0.06249936,0.006548024,0.4616657],"study_design_scores_gemma":[0.0001793505,0.0007393415,0.001104518,0.0000656164,0.00007074569,0.001056396,0.00007503827,0.8289031,0.1217255,0.02234598,0.02368325,0.00005114697],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0272052,0.0001586809,0.9644166,0.0001248841,0.00001634439,0.0001339475,0.0001433018,0.002413869,0.005387263],"genre_scores_gemma":[0.582635,0.0001609386,0.4121038,0.0002263837,0.00003963071,0.0004673495,0.0004875672,0.0004642918,0.003415006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005692805,"threshold_uncertainty_score":0.01904434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1284947865602946,"score_gpt":0.30524118060213,"score_spread":0.1767463940418354,"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."}}