MétaCan
Menu
Back to cohort
Record W2099409907 · doi:10.1109/jssc.2008.2011032

A Wideband Power Detection System Optimized for the UWB Spectrum

2009· article· en· W2099409907 on OpenAlexaff
Kenneth A. Townsend, J.W. Haslett

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2009
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNMOS logicWidebandTriodeRadio frequencyPower (physics)CMOSElectrical engineeringPhysicsDetectorElectronic engineeringPiecewise linear functionVoltageComputer scienceEngineeringCapacitorMathematicsTransistor

Abstract

fetched live from OpenAlex

A wideband radio-frequency (RF) power detection system is presented. The detection technique uses NMOS devices operating in the triode regime to generate an average current proportional to RF input power; this current is converted to voltage and amplified using a piecewise linear logarithmic approximation. Optimization of the NMOS devices is discussed, and a method of gain control is proposed for compensation of temperature and process variation. The power detector occupies an active area of 0.36 mm2in a 0.18 mum CMOS process and consumes 10.8 mW from the power supply. Error between the output and a linear-in-dB best-fit curve is plusmn2.4 dB for a 20 dB input range, when measured at discrete frequencies. The output response is frequency independent, varying by less than 1.8 dB for a fixed input power as frequency is swept across the UWB spectrum.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.013
GPT teacher head0.231
Teacher spread0.217 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Journal of Solid-State CircuitsSame topicRadio Frequency Integrated Circuit DesignFrench-language works237,207