Curvature-insensitive methodology for thermal-wave depth-profilometry in multi-layered curvilinear solids
Bibliographic record
Abstract
A generalized similarity normalization (SN) methodology for characterizing depth profiles of continuously varying thermophysical properties in curvilinear (cylindrical and spherical) solids is presented. Specifically, the principle and the physical mechanism of the elimination of the surface curvature effect from the overall photothermal signal is introduced based on theoretical models of cylindrical, spherical and flat solids with multi-layer structures. The effects of the relative values of radii of curvature of the curvilinear solid, the thickness of the inhomogeneous surface layer and the measurement azimuthal angle on the validity of the technique are discussed in detail. Experimental reconstructions of thermophysical depth profiles of hardened cylindrical steel rods of various diameters are performed based on both curvilinear theory and the equivalent flat surface theory. The reconstructed results are compared and validated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".