Material characterization with top-hat cw laser induced photothermal techniques: A short review
Bibliographic record
Abstract
In this work, we present a short review of the recent development of the theoretical models for top-hat cw laser induced spectroscopies of thermal lens and thermal mirror. With the same probe and top-hat excitation lasers, an apparatus is set up to concurrently measure both thermal lens and thermal mirror effects of transparent samples. With the theoretical models and the experimental apparatus, not only optical and thermal properties are measured, but also the fluorescence quantum coefficient and the temperature coefficient of the optical path length of a fluorescent sample are simultaneously determined with no need of any reference sample. Mechanical properties also could be measured. Opaque samples are also studied using top-hat cw laser thermal mirror and top-hat photothermal deflection techniques to determine thermal properties (e.g., thermal conductivity and unit volume specific heat). This work shows that the combined top-hat cw laser photothermal techniques are useful for nondestructive evaluation of both transparent and opaque samples with a less expensive non-TEM 00 Gaussian laser.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".