{"id":"W4410810570","doi":"10.1109/fccm62733.2025.00045","title":"Chronbench: An Incremental HDL Benchmark Suite","year":2025,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Suite; Benchmark (surveying); Computer science; Geology","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":[0.00169873,0.001030583,0.0002896398,0.001944886,0.0003455153,0.0006887875,0.001955981,0.0005436909,0.003870869],"category_scores_gemma":[0.00510902,0.0003537986,0.0005152237,0.002088488,0.0003576626,0.0008534473,0.0006293721,0.0008057595,0.0007634432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005934335,"about_ca_system_score_gemma":0.001149735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00388921,"about_ca_topic_score_gemma":0.007909794,"domain_scores_codex":[0.9987637,0.0002881379,0.0001201265,0.0001376065,0.0005350793,0.0001554271],"domain_scores_gemma":[0.9967651,0.00144338,0.0002347312,0.0006096069,0.0008145967,0.0001325232],"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":[0.001776403,0.001603417,0.03971704,0.00331188,0.0004554563,0.001843406,0.0005315797,0.3166726,0.06304677,0.02536448,0.2109851,0.3346918],"study_design_scores_gemma":[0.0007256155,0.002324515,0.02043378,0.0002454393,0.00022138,0.001074339,0.0004442634,0.6800422,0.1165681,0.01377443,0.1640066,0.0001394137],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6934677,0.002330243,0.1460963,0.0009223943,0.0005485694,0.001033342,0.05593524,0.04700905,0.05265713],"genre_scores_gemma":[0.6708645,0.001237188,0.1964088,0.0003264963,0.00008513233,0.0009364543,0.1154716,0.004375674,0.01029411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00388921,"threshold_uncertainty_score":0.01294935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004720689537096986,"score_gpt":0.2076050782237723,"score_spread":0.2028843886866754,"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."}}