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
This chapter aims to summarize the available data on regulation of cardiac development and stem cell differentiation by miRNAs. Heart malformations occur in as high as 1% of newborns, presenting a significant clinical problem in our modern world. The first functional organ in the embryo is the heart and cardiovascular system and the heart is susceptible to congenital defects more than any other organ. Both intrinsic and extrinsic factors determine the development of the cardiovascular system. miRNA was initially described as being fundamental for developmental biology first in nematode worms and then in phylogenically more advanced organisms. Many defects of the miRNA machinery are incompatible with correct and/or continued development. On the other hand, pluripotency and cellular differentiation are intricate biological processes that are coordinately regulated by a complex set of factors and epigenetic regulators. As in other tissues, a distinct set of miRNAs is specifically expressed in pluripotent embryonic stem cells. This chapter describes the involvement of miRNAs in normal cardiac development, in congenital heart disease and Down syndrome, and in determining stem cell fate. In particular, the roles of miR-1, miR-133, miR-130a and miR-138 in cardiac development are described as these miRNAs have been experimentally studied in detail.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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