A Diversity of Cell Types, Subtypes and Phenotypes in the Central Nervous System: The Importance of Studying Their Complex Relationships
Bibliographic record
Abstract
All the cell types in the central nervous system (CNS) cooperate to mediate proper development, function, and plasticity. Similarly, brain repair and neuroprotection, but also demyelination, synaptic loss and neurodegeneration, were increasingly shown to involve non-neuronal cells— both glial cells and peripheral immune cells—among the CNS parenchyma. Adding another degree of complexity, the non-neuronal cell populations are emerging as comprised of different subtypes, endowed with unique properties and functions at steady-state, and which can adopt various phenotypes upon exposure to homeostatic challenges. As a consequence, studying the multidirectional relationships between these different cell types, subtypes and phenotypes in the CNS is now required to provide insights into the mechanisms underlying physiological processes such as neuronogenesis, axon guidance,myelination, vascular formation and remodeling, regulation of neuronal activity, as well as synaptic formation, function and plasticity, and behavioral outputs, among other essential CNS functions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".