Standardization of postmortem human brainstem along the rostrocaudal axis to accommodate for inter-specimen structural heterogeneity
Bibliographic record
Abstract
There is increasing recognition of the critical need for postmortem studies of human brainstem tissues for elucidating the pathophysiology of neurological disorders. While the brainstem is critical for a myriad of functions it is relatively small with a complex organization of tracts and nuclei. So, interindividual heterogeneity in brainstem structure that can derive from tissue procurement or be related to anthropometric features like height or weight can greatly impact studies of brainstem structure and function. In the absence of explicit approaches to account for these sources of heterogeneity drawing inferences from interindividual comparisons can be challenging. This study used postmortem brainstem samples from well-characterized older decedents to systematically assess factors contributing to heterogeneity in the length of whole brainstem samples. These findings led to a standardized approach to reproducibly assign rostrocaudal levels, with standardization relying upon readily identifiable internal anatomic landmarks. We validated this approach using postmortem MRI imaging. Standardized brainstem length correlated positively with subject height and brain weight but not age of death. By providing a reference series, this study will facilitate the assignment of reproducible levels to individual histological sections or MRI images when full brainstem specimens are not available, promoting reproducibility within and across different studies.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".