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Record W2166419724 · doi:10.1109/newcas.2004.1358997

An investigation into transistor-based adiabatic logic styles

2004· article· en· W2166419724 on OpenAlexaff
Muhammad Arsalan, M. Shams

Bibliographic record

VenueThe 2nd Annual IEEE Northeast Workshop on Circuits and Systems, 2004. NEWCAS 2004. · 2004
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsCarleton University
Fundersnot available
KeywordsAdiabatic processPass transistor logicTransistorCMOSLogic gateAdiabatic circuitElectronic engineeringPower (physics)Computer scienceLogic familyElectrical engineeringLogic synthesisEngineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

Over the past decade, different adiabatic logic styles for low-power applications have been published. Due to the ever shrinking transistor sizes, devices are able to operate at lower potential differences. On the other hand, submicron technological phenomena like short-channel effect are gaining more influence in determining the behavior of devices. To account for these technological differences and advancements, this paper compares and analyzes the performance of various adiabatic logic styles in a uniform environment using a standard 0.18 /spl mu/m CMOS technology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.237
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2004
Admission routes1
Has abstractyes

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