Possible role of the cavernous sinus veins in cerebrospinal fluid absorption
Bibliographic record
Abstract
The purpose of this investigation was to enhance our understanding of cerebrospinal fluid (CSF) absorption pathways. To achieve this, Microfil (a coloured silastic material) was infused into the subarachnoid space (cisterna magna) of sheep post mortem, and the relevant tissues examined macroscopically and microscopically. The Microfil was taken up by an extensive network of extracranial lymphatic vessels in the olfactory turbinates. In addition however, Microfil also passed consistently through the dura at the base of the brain. Microfil was noted in the spaces surrounding the venous network that comprises the cavernous sinus, in the adventitia of the internal carotid arteries and adjacent to the pituitary gland. Additionally, Microfil was observed within the endoneurial spaces of the trigeminal nerve and in lymphatic vessels emerging from the epineurium of the nerve. These results suggest several unconventional pathways by which CSF may be removed from the subarachnoid space. The movement of CSF to locations external to the cranium via these routes may lead to its absorption into veins and lymphatics outside of the skull. The physiological importance of these pathways requires further investigation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".