Cuboids of Infrared Images Reduction
Bibliographic record
Abstract
The main idea of this scientific article is tomography usage. Projections of multidimensional signal carrying the information about the spatial structure of objects' thermal physic properties are represented by thermal tomograms obtained in active mode of test material surface heating by infrared radiation. Processing of a thermal tomogram is produced by solving the inverse thermal conductivity problem. This solution applies to cuboids of infrared images reduction class of problems. Because of reduction, we get the distribution image of thermal conductivity identified values on isotropic material surface (thermal tomogram) allowing revealing foreign inclusions in the heterogeneous object structure based on the contrast over thermal conductivity. Implementation of this idea is associated with certain difficulties due to the necessity of mathematical modeling of nonlinear thermal transients. The paper presents quartz sand thermal tomograms with temperature conductivity of 9 10-7 m2 s and thermal conductivity of -1 0.9 W m-1 K-1 which structure contains thermal insulation material - expanded foam, and thermally conductive material - aluminum.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".