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Record W2069767647 · doi:10.1109/lascas.2013.6519083

A configurable analog buffer dedicated to a wafer-scale prototyping platform of electronic systems

2013· article· en· W2069767647 on OpenAlexaff
Nicolas Laflamme-Mayer, Mohamad Sawan, Yves Blaquière

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversité du Québec à MontréalPolytechnique Montréal
Fundersnot available
KeywordsCMOSSlew rateComputer scienceTransistorBuffer amplifierBandwidth (computing)Electrical engineeringTopology (electrical circuits)VoltageEngineeringAmplifierTelecommunications

Abstract

fetched live from OpenAlex

A novel, configurable and compact CMOS analog buffer, dedicated to a wafer-scale prototyping platform for electronic systems is described in this paper. The proposed buffer architecture, made in a 0.18 μm CMOS technology, is based on complementary modified differential pairs combined with single current mirrors. This analog buffer can support a wide range of operating output voltages, from VDD- 150 mV down to VSS+ 150 mV using a 3.3 V power supply. This design offers a configurable slew-rate, which range from 66 up to 450 V/μs and a quasi unity gain for all programmed slew-rates. This feature allows the user to adjust the proposed buffer to fit its needs while limiting noise injection in the power supply as well as quiescent current. Moreover, the proposed analog buffer supports a -3 dB bandwidth from 74 up to 194 MHz. The low count of transistors, 21, yields to a very compact structure that uses only 0.001824mm2of silicon area.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2013
Admission routes1
Has abstractyes

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