Bibliographic record
Abstract
The vasculature is one of the most important and complex organs in the mammalian body. The first functional organ to form during embryonic development, the intricately branched network of endothelial and supporting periendothelial cells is essential for the transportation of oxygen and nutrients to and the removal of waste products from the tissues. Serious disruptions in the formation of the vascular network are lethal early in post-implantation development, while the maintenance of vessel integrity and the control of vessel physiology and hemodynamics have important consequences throughout embryonic and adult life. A full understanding of the signaling pathways of vascular development is important not just for understanding normal development but because of the importance of reactivation of angiogenic pathways in disease states. Clinically there is a need to develop therapies to promote new blood vessel formation in situations of severe tissue ischemia, such as coronary heart disease. In addition, there is considerable interest in developing angiogenic inhibitors to block the new vessel growth that solid tumors promote in host tissue to enhance their own growth. Already studies on the signaling pathways of normal vascular development have provided new targets for therapeutic intervention in both situations. Further understanding of the complexities of the pathways should help refine such strategies.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".