<title>Optical property determination of turbid media using frequency-domain infrared photothermal radiometry</title>
Bibliographic record
Abstract
Among diffusion methods, photothermal radiometry (PTR) has the ability to penetrate and yield information about an opaque medium well beyond the range of conventional optical imaging. Owing to this ability, pulsed-laser PTR has been extensively used in turbid media such as biological tissue to study the sub-surface deposition of laser radiation, a task which may be difficult or impossible for conventional optical methods due to excessive scattering and absorption. In this work, the optical and thermal properties of tissue- like materials are observed using frequency-domain IR photothermal radiometry. An approximate 3D heat conduction formulation with the use of 1D optical diffusion is developed to derive a turbid frequency-domain PTR model. The agreement in the absorption and transparent scattering coefficients of model phantoms is investigated. The present opto-thermal model for frequency-domain PTR may prove useful for non-contact, non-invasive, in situ measurement of optical properties of tissues and other multiply-scattering media.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".