Dissecting the Non-human Primate Brain in Stereotaxic Space
Bibliographic record
Abstract
The use of non-human primates provides an excellent translational model for our understanding of developmental and aging processes in humans(1-6). In addition, the use of non-human primates has recently afforded the opportunity to naturally model complex psychiatric disorders such as alcohol abuse(7). Here we describe a technique for blocking the brain in the coronal plane of the vervet monkey (Chlorocebus aethiops sabeus) in the intact skull in stereotaxic space. The method described here provides a standard plane of section between blocks and subjects and minimizes partial sections between blocks. Sectioning a block of tissue in the coronal plane also facilitates the delineation of an area of interest. This method provides manageable sized blocks since a single hemisphere of the vervet monkey yields more than 1200 sections when slicing at 50 microm. Furthermore by blocking the brain into 1cm blocks, it facilitates penetration of sucrose for cyroprotection and allows the block to be sliced on a standard cryostat.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".