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Record W4238977407 · doi:10.32920/ryerson.14649573.v1

Theoretical and Experimental Study of Single-Needle Thermal Conductivity Probe

2021· preprint· en· W4238977407 on OpenAlexfundno aff
Lam Dang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal conductivityMaterials scienceThermal ablationThermal conductionAnalytical Chemistry (journal)AblationChemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

<p>The thermal conductivities of materials (k<sub>m</sub>) are important in many fields such as agriculture, mining and biomedical engineering. For example, better knowing the k<sub>m</sub> values of biomaterials can be useful in radiofrequency ablation (RFA) to treat and/or cure tumor and cancer cells (Liu <em>et al</em>. [3]). Thermal conductivity probes (TCPs) have proven to be very attractive in obtaining relatively accurate k<sub>m</sub> values due to their inline measurements, inexpensiveness, portability, and versatility. </p> <p>However, due to the vast number of designs and applications of TCPs, sources of errors with using the probes are diverse. As a result, in this thesis, possible sources of errors in TCPs (single needle) were investigated. The sources include probe sizes, heating powers, sampling media, selection of TCP materials, location of the thermocouple, axial heat conduction, thermal contact resistance, initiating time t<sub>0</sub>, decision to use heating or cooling period for km calculations and tolerance in the thermal properties of epoxy.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.563

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 head0.020
GPT teacher head0.245
Teacher spread0.224 · 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 teacher head, 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

Citations1
Published2021
Admission routes1
Has abstractyes

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