Fluorescence diffuse optical tomography measurements for tissue engineering
Bibliographic record
Abstract
Currents eorts in tissue engineering (TE) are directed towards growing 3D volumes of tissues. In response to TE needs, we are developing a non-invasive technique based on fluorescence diuse optical tomography (FDOT) to image in 3D, via fluorescence labelling, the formation of micro-blood vessels in tissue cultures grown on biodegradable scaolds in bioreactor conditions. In the present work, we use a non-contact FDOT setup developed for small animal imaging for our measurements. We present experimental results showing the feasability to localize a fluorophore-filled 500μm capillary immersed in a scattering medium contained in a cylindrically-shaped glass tube. These conditions are representative of experiments to be carried on real tissue cultures. Time-resolved scattering-fluorescence measurements are made via Time-Correlated Single Photon Counting (TCSPC) and we use numerical constant fraction discrimination (NCFD) to obtain primary localization information from our time-resolved data.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".