Compartmentation of the mouse cerebellar cortex by neuronal calcium sensor‐1
Bibliographic record
Abstract
Neuronal calcium sensor-1 (NCS-1) is a member of the EF-hand calcium-binding protein superfamily, which is considered to modulate synaptic transmission and plasticity. The detailed distribution of NCS-1 was analyzed in the mouse cerebellar cortex. In coronal sections, the NCS-1 immunostaining displayed characteristic parasagittal banding pattern in the Purkinje cell layer and molecular layer, while there were no apparent bands in the granule cell layer. The alternating positively and negatively NCS-1-labeled Purkinje cell clusters contributed to this cerebellar compartmentation. In contrast, stellate-basket cells were uniformly NCS-1-positive throughout the cerebellum. Immunofluorescent double staining showed that NCS-1 and zebrin II exhibited a similar parasagittal banding pattern. Then, we performed mapping of NCS-1- and/or zebrin II-labeled Purkinje cell somata using seven sequential coronal sections. NCS-1-positive/zebrin II-positive Purkinje cell clusters were seen throughout the cerebellum, but NCS-1-positive/zebrin II-negative Purkinje cells were exceedingly rare. On the other hand, NCS-1-negative/zebrin II-positive Purkinje cell clusters were found in anterior lobule vermis and paraflocculus, whereas they were rarely seen in posterior lobules. The digitized quantitative analysis showed close relationship between NCS-1 and zebrin II immunoreactivity in the molecular layer. The correspondence between NCS-1 and zebrin II demonstrated here indicates a novel anteroposterior difference of cerebellar compartmentation and provides fundamental information of cerebellar organization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".