{"id":"W4312889722","doi":"10.1109/tcad.2022.3226668","title":"Bulls-Eye: Active Few-Shot Learning Guided Logic Synthesis","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Science Foundation","keywords":"Shot (pellet); Computer science; Artificial intelligence; Materials science","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":[0.001177973,0.001152705,0.001108145,0.0007348179,0.0004230383,0.000977647,0.002261682,0.00155318,0.004478726],"category_scores_gemma":[0.002374873,0.0006533991,0.0007506987,0.0004485013,0.0009926145,0.001454365,0.001182299,0.001579923,0.0009728164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029673,"about_ca_system_score_gemma":0.001099829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004746696,"about_ca_topic_score_gemma":0.01041305,"domain_scores_codex":[0.9994728,0.0001109573,0.00002327395,0.0001843143,0.0001587031,0.00005003097],"domain_scores_gemma":[0.9989265,0.0007047715,0.00005667898,0.0001580262,0.0001056357,0.00004836623],"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":[0.0004615116,0.0002194259,0.0007948345,0.0002141902,0.00009360426,0.0001708347,0.0001609882,0.6361076,0.02254768,0.009817883,0.00620749,0.323204],"study_design_scores_gemma":[0.00001311722,0.00002740331,0.00003500711,0.000003994726,0.000005338076,0.00001208384,0.000005822178,0.9919822,0.003746028,0.003557437,0.0006063896,0.000005239213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02697556,0.0005412998,0.9604383,0.0001814963,0.00006256613,0.00007962622,0.0001592557,0.007743711,0.003818246],"genre_scores_gemma":[0.5043185,0.0002091232,0.484809,0.0006003267,0.00004529445,0.0001689533,0.0009250309,0.001139069,0.007784785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004746696,"threshold_uncertainty_score":0.01498282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0656011685826022,"score_gpt":0.2561631510089744,"score_spread":0.1905619824263722,"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."}}