Linear relationship found by magnetic resonance imaging between cerebrospinal fluid volume and body weight in dogs
Bibliographic record
Abstract
Despite numerous studies on cerebrospinal fluid (CSF) and its importance during hydrocephalus or myelography, no reliable values exist about its overall volume in dogs. In this study, our aim was to measure the intracranial (IC) volume of CSF in dogs and assess its possible relationship with body size and the symmetry of the lateral ventricles. We ran a 3D magnetic resonance imaging (MRI) sequence on the central nervous system of 12 healthy, male mongrel dogs between 3-5 years of age and 7.5-35.0 kg body weight. A validated semiautomatic segmentation protocol was implemented to segment the CSF and measure its volume. Values for the volume of the ventricular compartment were between 0.97 and 2.94 ml, with 62.1 ± 11.7% in the lateral ventricles, 17.6 ± 4.9% in the third ventricle, 4.9 ± 1.6% in the aqueductus mesencephali and 15.5 ± 6.6% in the fourth ventricle. In 11 cases a significant asymmetry was found between the lateral ventricles. The results suggest that it may be normal for a dog to have one of the lateral ventricles 1.5 times larger than the other. The correlation between body weight and CSF volume was linear, indicating that the current dosage protocols for myelography, based on a hypothetical proportional relationship with body weight, may have to be revised.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".