Comparative morphology of the rat optic nerve using light and electron microscopy
Bibliographic record
Abstract
Optic nerve fibers are the axons of retinal ganglion cells, and as such they can provide information about the visual acuity and sensitivity capabilities of an animal. Consistent optic nerve fiber counts are not currently available for most animals. In this study, using light microscopy, we counted optic nerve fibers for 7 nerves from 4 adult Sprague‐Dawley rats. Using unbiased stereology we counted 4 adjacent sections of each nerve at 1000X, each using a different staining technique, including Bielschowsky's silver impregnation , Bodian's protagarol , Luxol Fast Blue stain, and a combination Bodian's protagarol and Luxol Fast Blue. We obtained counts of 75,000 to 90,000 fibers, with a fiber size range of 0.1μm to 5μm. We also examined preliminary electron micrographs of one Sprague‐Dawley rat optic nerve at magnifications up to 10,000X. Published counts of the pigmented rat optic nerve fibers using electron microscopy are 120,000, with a size range of 0.4μm to 5μm. This is significantly higher than our light microscopy counts. However, using EM at 10,000X we observe myelinated fibers as small as 0.02.μm. This discrepancy in fiber numbers calls into question which methodology is most suitable for counting myelinated fibers within the optic nerve. Grant Funding Source : Kenneth A. Suarez fellowship
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".