{"id":"W1897919766","doi":"10.1109/edac.1991.206437","title":"A framework for hierarchical performance analysis (of VLSI)","year":2002,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Hierarchy; Very-large-scale integration; Software; Data mining; Hierarchical database model; Theoretical computer science; Programming language; Embedded system","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":[0.003236914,0.001373782,0.0009021878,0.00232608,0.001166136,0.003759308,0.003037058,0.001295347,0.00686113],"category_scores_gemma":[0.004583866,0.0009912495,0.002847748,0.001942147,0.003159768,0.003877052,0.00295863,0.002711687,0.002724096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001823751,"about_ca_system_score_gemma":0.001981012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005663713,"about_ca_topic_score_gemma":0.004314274,"domain_scores_codex":[0.9976641,0.0007493799,0.0001807225,0.0004043646,0.0007807722,0.0002205815],"domain_scores_gemma":[0.9984788,0.0005621169,0.0001075531,0.0004805081,0.0002932496,0.00007769458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001004635,0.0000134086,0.0001424105,0.0001094338,0.00002299738,0.00008835585,0.0002271239,0.01616935,0.001145358,0.9388629,0.003286947,0.0399217],"study_design_scores_gemma":[0.00001478193,0.00002557023,0.0001552103,0.00009178464,0.00003129836,0.000147941,0.00004825869,0.1168179,0.001050993,0.8114542,0.07013527,0.00002691064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003510296,0.0003215888,0.9953071,0.0001164568,0.00002904619,0.00003498013,0.00006950841,0.0004573749,0.003312838],"genre_scores_gemma":[0.02670613,0.0006088329,0.9691244,0.0001357155,0.0001376396,0.0002295487,0.0002879024,0.0002863626,0.002483577],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00686113,"threshold_uncertainty_score":0.02295274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0209822226900377,"score_gpt":0.2282634826205101,"score_spread":0.2072812599304724,"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."}}