Bibliographic record
Abstract
The interstitium surrounds the capillaries. It consists of cells that are embedded in a matrix of extracellular biomacromolecules known as the extracellular matrix (ECM; see Section 2.4). Depending on the tissue, the cells can account for a large fraction of interstitial volume or can be relatively few in number. An important task of the resident cells, or at least of some subpopulation of the resident cells, is to synthesize and secrete the extracellular biopolymers that make up the ECM. Interstitial fluid flow We have seen in Section 4.4 that there is a continuous transport of fluid from capillary blood into the lymphatic system, via the interstitium. The net flow rate from capillaries to lymphatics is determined by the driving potential (the difference in p - π between the capillaries and the lymphatics), as well as the hydrodynamic resistance of the intervening interstitium. Interstitial flow resistance is therefore very important in fluid homeostasis, or maintaining proper tissue hydration. Intuition suggests that interstitial flow resistance should depend on tissue structure, or more specifically on: the local concentrations of ECM components the local number of cells per unit tissue volume the manner in which cells and ECM components are packed together. Cells and ECM components are packed together in a random manner. Because of this random character, it is challenging to describe detailed flow patterns on a cellular or subcellular length scale.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.019 |
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".