{"id":"W2143451225","doi":"10.1109/iccd.1989.63372","title":"Magnitude classes in switch-level modeling","year":2003,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Magnitude (astronomy); Consistency (knowledge bases); Computer science; Gaussian; Electronic circuit; Gaussian elimination; Voltage; Algorithm; Topology (electrical circuits); Mathematics; Electrical engineering; Artificial intelligence; Physics; 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":[0.001050905,0.000541237,0.0003321071,0.0009109279,0.0004129715,0.001912588,0.0008854699,0.0007199727,0.004552897],"category_scores_gemma":[0.004663938,0.0004326721,0.0005283336,0.0005476672,0.0008699106,0.003597795,0.0008269846,0.001511568,0.0007559814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008139822,"about_ca_system_score_gemma":0.0004121271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001049974,"about_ca_topic_score_gemma":0.0008133732,"domain_scores_codex":[0.9994624,0.0001542886,0.00002728331,0.00007190553,0.0002347783,0.00004924438],"domain_scores_gemma":[0.9984205,0.001039207,0.0001384379,0.0002075599,0.0001524977,0.00004186597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004538512,0.00002673277,0.0007922581,0.0000648367,0.000009502366,0.00006026145,0.0001353891,0.1893404,0.004358531,0.7666402,0.001191869,0.03733462],"study_design_scores_gemma":[0.00001045085,0.00003779507,0.0002915961,0.00002642752,0.00001110496,0.00006888723,0.00003664827,0.5911877,0.003867309,0.3921524,0.01229013,0.00001962438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02980298,0.0005080554,0.9356463,0.0006286504,0.00009832324,0.00005393751,0.0001054917,0.0006028048,0.03255345],"genre_scores_gemma":[0.8285565,0.001382006,0.1511598,0.0002985344,0.0001898358,0.0001867936,0.0002244757,0.000406349,0.01759568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004552897,"threshold_uncertainty_score":0.01523095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0308445768551316,"score_gpt":0.2141425716056233,"score_spread":0.1832979947504917,"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."}}