Theoretical and Experimental Study of Single-Needle Thermal Conductivity Probe
Bibliographic record
Abstract
<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>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".