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Record W2161785572 · doi:10.1109/tim.2008.2008861

CCC Bridge With Digitally Controlled Current Sources

2008· article· en· W2161785572 on OpenAlexaff
C A Sánchez, Barry Wood, A.D. Inglis

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsResistorBridge (graph theory)ComparatorNoise (video)OmegaElectrical engineeringJohnson–Nyquist noiseCurrent (fluid)Function (biology)Transfer functionPhysicsElectronic engineeringAnalytical Chemistry (journal)Computer scienceEngineeringChemistryArtificial intelligenceDetector

Abstract

fetched live from OpenAlex

We have built a cryogenic current comparator (CCC) resistance bridge for the comparison of standard resistors in the range of 1 Omega-100 kOmega. The use of fully programmable current sources allows for smooth polarity reversals, regardless of the time constant of each side of the bridge. We measured a CCC transfer function of 2.25 muA middotturn/phi0and a noise level of 54 pA middot turn/radic(Hz) at 1 Hz, with a 1/f corner of about 0.6 Hz. Two different readout schemes were implemented and compared with good agreement. We performed a few measurements to assess the accuracy of the bridge and evaluated all the significant sources of error. The total uncertainty of the bridge is estimated to be 2.6 parts in 109between 1 Omega and 10 kOmega.

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)0.002
metaresearch head score (Gemma)0.005
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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.038
GPT teacher head0.236
Teacher spread0.198 · 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
GenreMethods

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

Citations15
Published2008
Admission routes1
Has abstractyes

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