Theoretical, experimental, and computational aspects of optical property determination of turbid media by using frequency-domain laser infrared photothermal radiometry
Bibliographic record
Abstract
In this work, the optical and thermal properties of tissuelike materials are measured by using frequency-domain infrared photothermal radiometry. This technique is better suited for quantitative multiparameter optical measurements than the widely used pulsed-laser photothermal radiometry (PPTR) because of the availability of two independent signal channels, amplitude and phase, and the superior signal-to-noise ratio provided by synchronous lock-in detection. A rigorous three-dimensional (3-D) thermal-wave formulation with a 3-D diffuse and coherent photon-density-wave source is applied to data from model phantoms. The combined theoretical, experimental, and computational methodology shows good promise with regard to its analytical ability to measure optical properties of turbid media uniquely, as compared with PPTR, which exhibits uniqueness problems. From data sets obtained by using calibrated test phantoms, the reduced optical scattering and absorption coefficients were found to be within 20% and 10%, respectively, of the values independently derived by using Mie theory and spectrophotometric measurements.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".