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Record W4253805044 · doi:10.32920/ryerson.14653422

Guarded hot plate apparatus design and construction for thermal conductivity measurements

2021· preprint· en· W4253805044 on OpenAlexaff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHot plateThermal conductivityHeat fluxMaterials scienceHeat transferMetreHeat flowThermalThermal conductivity measurementMeasure (data warehouse)Thermal resistanceFlow (mathematics)Flux (metallurgy)MechanicsComposite materialThermodynamicsPhysicsComputer science

Abstract

fetched live from OpenAlex

A Guarded Hot Plate (GHP) appartus was designed and built for high temperatue applications, consistent with or better than the established standards. This apparatus consists of a hot and a cold plate, attached to a frame, which allows the plates to be tilted from horizontal to vertical and configured for heating from the top to the bottom. The plates are independently heated by passing heat transfer fluid through a flow distribution system consisting of manifolds and internal flow passages, machined in each plate. Attached to the hot plate are an electrically heated heater plate and a heat flux meter, configured consistent with the hybrid method for measuring heat flux. This apparatus is designed to measure thermal conductivity of soils at different moisture contents and for temperatures ranging from -20⁰C to 200⁰C. An error analysis for the thermal conductivity measurement shows a conservative estimate of the bias error to be around [plus or minus] 2%.

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)0.003
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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.007

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 head0.093
GPT teacher head0.275
Teacher spread0.183 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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