Veins and Lymphatics 2014; volume 3:4195 [page 74] [Veins and Lymphatics 2014; 3:4195]
Bibliographic record
Abstract
Last January The Lancet published the arti-cle by Traboulsee et al. Prevalence of extracra-nial venous narrowing on catheter venography in people with multiple sclerosis, their sibil-ings, and unrelated healthy controls: a blinded, case control study. These Authors confirmed the presence of chronic cerebrospinal venous insufficiency with a high prevalence of about 70 % in the Canadian population, but without significant differences between patients and healthy controls, yet. However, they used a cri-terion never published to assess stenosis, in alternative to the classic measurement of the diameter in the segment immediately preced-ing the narrowest point. Traboulsee et al. measure the stenosis along the entire length of the internal jugular vein, by comparing the maximum diameter with the narrowest point. It has been demonstrated, from normal anato-my findings, how the jugular bulb diameter normally exceeds 50 % of the minimum diame-ter of the internal jugular vein, clearly showing the reason why Traboulsee et al. did not find significant differences between people with multiple sclerosis, their sibilings, and unrelat-ed healthy controls. Furthermore, as the outcome measure of Traboulsee et al., wall stenosis is a neglected part of primary venous obstruction, because in the majority of cases obstruction is the conse-quence of intraluminal obstacles, as a consid-erable part of truncular venous malformations, and/or compression; rarely of external hypopla-sia. Finally, several recently published methods can be adopted for objective assessment of restricted jugular flow in course of chronic cerebrospinal venous insufficiency, by the means of non invasive magnetic resonance imaging, ultrasound and plethysmography. This may help us in improving the assess-ment of cerebral venous return in the near future.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.167 | 0.039 |
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".