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
Over the last decades, tissue engineering has demonstrated an unquestionable potential to regenerate damaged tissues and organs. Some tissue-engineered solutions recently entered the clinics (eg, artificial bladder, corneal epithelium, engineered skin), but most of the pathologies of interest are still far from being solved. The advent of stem cells opened the door to large-scale production of "raw living matter" for cell replacement and boosted the overall sector in the last decade. Still reliable synthetic scaffolds fairly resembling the nanostructure of extracellular matrices, showing mechanical properties comparable to those of the tissues to be regenerated and capable of being modularly functionalized with biological active motifs, became feasible only in the last years thanks to newly introduced nanotechnology techniques of material design, synthesis, and characterization. Nanostructured synthetic matrices look to be the next generation scaffolds, opening new powerful pathways for tissue regeneration and introducing new challenges at the same time. We here present a detailed overview of the advantages, applications, and limitations of nanostructured matrices with a focus on both electrospun and self-assembling scaffolds.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it