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Record W2154308178 · doi:10.1109/lmwc.2009.2024844

Static Phase Offset in a Multiplying Phase Detector

2009· article· en· W2154308178 on OpenAlex
John Patten Carr, Brian Frank

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2009
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsQueen's University
Fundersnot available
KeywordsOffset (computer science)DetectorParasitic extractionCMOSElectronic engineeringPhase detectorPhase (matter)PhysicsDC biasElectrical engineeringComputer scienceComputational physicsEngineeringOpticsVoltageQuantum mechanics

Abstract

fetched live from OpenAlex

This article analyzes the static phase offset DeltaPhi <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> of a Gilbert cell phase detector, and attributes the majority of the offset to intrinsic channel transit time. A 6.5 GHz phase detector fabricated in a standard 0.18 mum CMOS technology is used for the study. The static phase offset is broken down into layout and intrinsic contributions, and a simple model is used to calculate the intrinsic component. The use of analytical equations for current and intrinsic phase offset results in prediction of the intrinsic static phase offset to within 12% for the current ranges considered. The use of the intrinsic model with extracted parasitics is then shown via analysis, simulation and experimental data to be useful in predicting the phase detector static phase offset. The analysis, confirmed by measurements, indicates the degree to which the static phase offset can be reduced by increasing the tail bias current.

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.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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