Characteristics of time-domain optical coherence tomography profiles generated from blood–saline mixtures
Bibliographic record
Abstract
Time-domain optical coherence tomography (OCT) employing a 1300 nm broadband source is used to study flowing blood-saline mixtures with blood concentration ranging from 20% to 100%. The study emphasizes the characteristics of the recorded OCT signal and its connection with the properties of the corresponding fluids. There are three regions with distinct properties along the compounded OCT profiles showing the signal dependence on depth. The recorded OCT signal increases for the first 80 microm into the fluid. The flow characteristics of the solution and the average spatial orientation of the blood cells can be extracted from this region of the OCT profile. In the second region, the OCT signal decreases with depth into the sample. An admixture of quasi-ballistic light detected after a single reflection and light recorded after undergoing multiple-scattering interactions with blood cells contributes to the signal recorded in this region. As a consequence, the attenuation of OCT signal with depth into the sample shows a weak dependence on the concentration of blood over this region. The third region starts at a depth of approximately 0.6 mm within all the studied blood-saline mixtures. OCT signal recorded from this region is dominated by light detected after multiple-scattering interactions with blood cells. This region of the OCT profile is characterized by a reduced rate of attenuation with depth compared to the rate recorded along the second region of the compounded profile. A geometrical method is used to estimate the contribution from multiple-scattered light to the OCT signal. The multiple-scattered component shows a parabolic dependence on blood concentration with a maximum contribution at a blood concentration of 55%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".