Flow of blood-saline mixtures studied by time-domain optical coherence tomography
Bibliographic record
Abstract
In-vitro analysis of flowing blood-saline mixtures is performed by time-domain optical coherence tomography imaging. The mixtures contain blood in concentrations ranging from 100% to 20%. For each image, a corresponding compounded profile is obtained by adding one thousand adjacent A-scans. The compounded profiles are used for characterizing the optical coherence tomography signal as it propagates within the studied blood-saline mixtures. The results obtained point toward the possibility of acquiring intra-vascular images of arterial tissue that is located behind slabs of flowing blood-saline. A threshold in the propagation distance beyond which the recorded signal becomes dominated by its multiple scattered components is established along the compounded profiles. The threshold location, at a depth of ~0.6 mm, is independent of blood concentration. Further investigation of the compounded profiles reveals that the region extending to a maximum depth of about 200 μm from the point where the probing beam enters blood-saline mixtures could reveal information about the flow regime. This opens the possibility of another application for time-domain optical coherence tomography in intravascular imaging: assessing the flow regime, i.e. laminar or turbulent.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".