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A Digitized Thermal Conductivity Measurement System for 3-Omega Sensors

2025· article· W7124839574 on OpenAlexaff
Ethan A. E. Garnier, Brandon C. Brown, Chris D. Rouse

Bibliographic record

Venuenot available
Typearticle
Language
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
Fundersnot available
KeywordsThermal conductivityThermal conductivity measurementSystem of measurementInstrumentation (computer programming)SoftwareMeasure (data warehouse)Interface (matter)Temperature measurementThermal

Abstract

fetched live from OpenAlex

Experimental 3-omega setups for measuring thermal conductivity often rely on costly instrumentation and lack a coherent interface. This paper proposes a relatively low cost and compact digitized system for measuring the thermal conductivity of samples using 3-omega sensors that streamlines testing while providing the measurement quality of traditional setups. The system features minimal analog hardware that can connect to any 3-omega sensor and provides a simple software interface to initiate and accumulate 3-omega tests. The design of this system is presented and validated by measuring the thermal conductivity of several dielectric fluids to within 2% of expected values. This system enables 3-omega testing outside of lab environments and promotes commercialization of the technique.

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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.055
GPT teacher head0.263
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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