Diffuse photon density wavefront speed as a contrast for tomographic imaging of heterogeneous diffusive media
Bibliographic record
Abstract
An imaging algorithm is implemented for tomographically reconstructing contrast maps of the space variant speed of diffuse photon density wavefronts (DPDWFs) propagating in biological tissue-like diffusing media. This speed serves as a novel contrast not previously exploited in the literature. The algorithm employs early photon arrival times (EPATs) extracted from a set of time domain measurements. A relationship between EPATs and the speed of DPDWFs is exploited as the forward model. The forward model and its use in an inverse problem are supported by experimental results. These are carried out for 3D media with tissue-like optical properties. The resulting inverse problem is formulated as a set of algebraic equations and solved within a constrained linear least squares framework. The results indicate that the algorithm provides tomographic information on heterogeneities locations and distributions.
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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 | 0.000 | 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 | 0.000 |
| 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".