Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human beings are greatly preoccupied with the unavoidable nature of aging. While the biological processes of senescence and aging are the subjects of intense investigations, the molecular mechanisms linking aging with disease and death are yet to be elucidated. Tissue engineering offers new models to study the various processes associated with aging. Using keratin 19 as a stem cell marker, our studies have revealed that stem cells are preserved in human skin reconstructed by tissue engineering and that the number of epithelial stem cells varies according to the donor's age. As with skin, human corneas can also be engineered in vitro. Among the epithelial cells used for reconstructing skin and corneas, significant age-dependent variations in the expression of the transcription factor Sp1 were observed. Culturing skin epithelial cells with a feeder layer extended their life span in culture, likely by preventing Sp1 degradation in epithelial cells, therefore demonstrating the pivotal role played by this transcription factor in cell proliferation. Finally, using the human tissue-engineered skin as a model, we linked Hsp27 activation with skin differentiation.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it