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Record W1503007228 · doi:10.1109/tim.2003.816852

Experience with high-output-resistance MJTC AC-DC transfer standards at high frequencies

2003· article· en· W1503007228 on OpenAlexaff
P.S. Filipski, Michael Boecker

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsThermopileConvertersMaterials sciencePlanarTemperature measurementSiliconElectrical engineeringThermal resistanceOptoelectronicsElectronic engineeringHeat transferEngineeringVoltagePhysicsComputer scienceOpticsMechanics

Abstract

fetched live from OpenAlex

The heater-thermopile insulation of planar, thin-film, multijunction thermal converters decreases at high frequencies due to the residual conductivity of the silicon chip. This may cause a change in their intrinsic AC-DC transfer difference, as well as an interaction with the measurement circuit, resulting in increased errors of measurements. This paper discusses the sources of these errors and the methods of their reduction. It is postulated that the AC-DC transfer differences of such converters need to be explicitly defined under specific measurement conditions.

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)0.019
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0030.006
Open science0.0040.002
Research integrity0.0020.004
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 head0.022
GPT teacher head0.230
Teacher spread0.209 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

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