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Record W1961930787 · doi:10.1109/iscas.2003.1205659

Performance characteristics of an ultra-low power VCO

2003· article· en· W1961930787 on OpenAlexafffund
M. Jamal Deen, M.H. Kazemeini, Sasan Naseh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsMcMaster University
FundersCMC Microsystems
KeywordsVoltage-controlled oscillatorCMOSElectrical engineeringTransistorVoltageLow voltagePower (physics)Electronic engineeringUltra low powerEngineeringMaterials sciencePhysicsPower consumption

Abstract

fetched live from OpenAlex

A CMOS voltage controlled oscillator (VCO) with ultra-low power capabilities is described. A discussion of the VCO's performance characteristics and modeling in terms of simple physics-based expressions is presented. The oscillators have been designed in a commercial 0.18 /spl mu/m CMOS technology and the transistors in the VCOs operate from weak to strong inversion modes at supply voltages from 80 mV to 1.8 V. A new and important feature of this VCO is the use of the substrate voltage as an additional control for the frequency tunability. The detailed experimental results and comparison to calculations are presented and discussed.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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

Citations46
Published2003
Admission routes2
Has abstractyes

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Same topicAdvancements in PLL and VCO TechnologiesFrench-language works237,207