Regularized phase tomography enables study of mineralized and unmineralized tissue in porous bone scaffold
Bibliographic record
Abstract
Regularized phase tomography was used to image non-calcified fibrous matrix in in vitro cell-cultivated porous bone scaffold samples. 3D micro-architecture of bone and bone scaffold has previously been studied by micro-computed tomography, synchrotron radiation (SR) micro-computed tomography and microdiffraction. However, neither of these techniques can resolve the low-calcified immature pre-bone fibrous structures. Skelite porous scaffold discs were seeded with osteoblasts, a combination of osteoblast and pre-osteoclasts and, as controls, with pre-osteoclasts only, and then cultivated for 8 weeks. They were subsequently imaged using SR propagation-based phase contrast imaging. Reconstructions using a regularized holographic phase tomography approach were compared to standard (absorption) SR micro-computed tomography, which show that quantitative analysis, such as volume and thickness measurements, of both the calcified fraction and the immature bone matrix in the reconstructed volumes is enabled. Indications of the effect of this type of culture on Skelite, such as change in mineralization and deposit of mature bone on the walls of the scaffold, are found. The results are verified with a histological study.
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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 | 0.000 |
| 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) | 0.001 | 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".