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
Stem cell‐derived 3D tissues such as spheroids are excellent models for investigating mechanisms of tissue formation and responses to physiological and mechanical cues. Neuronal spheroids, also known as neurospheres, have attracted particular interest. A lot is now known about the differentiation and maturation of neurospheres, as well as their responses to biochemical cues. However, understanding about their mechanical properties pales in comparison, which is all the more galling in light of newfound insights about how mechanical stimuli trigger the onset of neurodegenerative conditions. Herein, formative steps are taken to fill this knowledge gap. Neurospheres are generated from murine neural stem cells and are subjected to compressive forces. It is observed that neurospheres exhibit stress relaxation under static compression and viscoelastic behavior at low strains. The suitability of the Tatara model for characterizing the mechanical properties of neurospheres is also evaluated. The study is the first study of its kind to investigate the mechanical properties of in vitro 3D tissues. Moreover, the methodologies developed in the study can also be used to improve the quality and safety of cell and tissue biomanufacturing processes.
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) | 0.000 | 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) | 0.000 | 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