{"id":"W2032888474","doi":"10.1109/tvlsi.2014.2334492","title":"New Analytic Model of Coupling and Substrate Capacitance in Nanometer Technologies","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Advancements in Semiconductor Devices and Circuit Design","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Canada Foundation for Innovation","keywords":"Capacitance; Computation; Nanometre; Coupling (piping); Electronic engineering; CMOS; Computer science; Substrate (aquarium); Integrated circuit; Substrate coupling; Algorithm; Computational science; Materials science; Optoelectronics; Engineering; Physics; Nanotechnology; Layer (electronics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002526057,0.000628897,0.0004426263,0.0006364077,0.0002785651,0.0005822911,0.001535229,0.001082014,0.001913214],"category_scores_gemma":[0.001119145,0.0003181988,0.0005312306,0.0007396907,0.0003380212,0.001915979,0.0003345231,0.0006506615,0.000663103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008767014,"about_ca_system_score_gemma":0.0007134812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002572497,"about_ca_topic_score_gemma":0.002106974,"domain_scores_codex":[0.9996877,0.00004893984,0.00001143683,0.00005962226,0.0001565758,0.00003576335],"domain_scores_gemma":[0.9998298,0.00006182287,0.0000254212,0.00002880729,0.00004528056,0.000008880748],"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":[0.00002186054,0.0000363345,0.0006261306,0.0001238162,0.00003568906,0.0003154913,0.0001249751,0.8341931,0.04573896,0.09033856,0.001513541,0.02693149],"study_design_scores_gemma":[0.000002047516,0.000009606858,0.00007058268,0.000003223383,0.00000455997,0.00006200823,0.00000589224,0.9938189,0.001213755,0.003518167,0.001286219,0.000004901712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01154789,0.0004658888,0.9821329,0.0001384114,0.00004084739,0.00003402884,0.00008802328,0.0003961019,0.005155996],"genre_scores_gemma":[0.744846,0.002049995,0.2413501,0.000288422,0.00008957188,0.0002931389,0.0002905288,0.0002998765,0.01049241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002572497,"threshold_uncertainty_score":0.006400347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767460702746909,"score_gpt":0.2188560039933465,"score_spread":0.2011813969658774,"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."}}