{"id":"W2164346795","doi":"10.1109/ccece.1998.682547","title":"An ordering-insensitive methodology for efficient DCVS circuit synthesis","year":2002,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Binary decision diagram; Cascode; Electronic circuit; Influence diagram; Computer science; Variable (mathematics); Network analysis; Diagram; Binary number; Topology (electrical circuits); Voltage; Algorithm; Decision tree; Mathematics; Transistor; Data mining; Engineering; Electrical engineering; Arithmetic","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":[0.0004188488,0.0005164027,0.0003588442,0.0007840056,0.0004322003,0.0006373482,0.0006629814,0.0002851137,0.002251348],"category_scores_gemma":[0.0008713262,0.0003493753,0.0004581559,0.0006318716,0.0003600564,0.0005471389,0.0004246149,0.0006797998,0.0006595691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005733857,"about_ca_system_score_gemma":0.0009207741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009408004,"about_ca_topic_score_gemma":0.001524884,"domain_scores_codex":[0.9994569,0.0001006857,0.00004599218,0.00007756663,0.0002780384,0.00004067747],"domain_scores_gemma":[0.9996389,0.0001105528,0.00003943614,0.0001057587,0.00009453167,0.00001085662],"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":[0.0001003814,0.0001013125,0.0003491956,0.0003371427,0.00004178158,0.0002182723,0.0001356429,0.06550156,0.2099147,0.1413394,0.005133746,0.5768268],"study_design_scores_gemma":[0.00008774534,0.0002691014,0.0003799402,0.00007817171,0.00008876348,0.0005585601,0.00004044668,0.6035788,0.2611667,0.06544358,0.068245,0.00006323135],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004994092,0.0001760006,0.9910453,0.00004725034,0.00003252902,0.00005894448,0.00005730666,0.0008046331,0.002784023],"genre_scores_gemma":[0.140155,0.0003660147,0.8550724,0.00008660348,0.00003048226,0.0001879917,0.0003830436,0.0001620196,0.003556311],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002251348,"threshold_uncertainty_score":0.007531524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07250855037253919,"score_gpt":0.2558728829704698,"score_spread":0.1833643325979307,"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."}}