A moment’s pause: putative nucleosome-based influences on MeCP2 regulationThis paper is one of a selection of papers published in this Special Issue, entitled 30th Annual International Asilomar Chromatin and Chromosomes Conference, and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
There has been a hotbed of activity surrounding MeCP2 research in the past number of years. Despite better characterizing the functions and nature of this protein, it has become abundantly clear that MeCP2 is involved in far more complex activities than perhaps initially anticipated. Recent publications have shown that MeCP2 is dynamically post-translationally modified, and it is possible that these marks permit MeCP2 to inhabit very diverse chromatin environments. It is also of interest to consider how nucleosome composition differs in these varying chromatin regions, and how the chromatin template itself contributes to diversifying the regulatory roles of MeCP2. These will be critical points to examine when seeking to understand how MeCP2 behaviour differentiates in tissues other than the brain. By understanding the chromatin and (or) tissue context in which MeCP2 interacts, it may be possible to discern the specific etiology of diseases linked to MeCP2 dysfunction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.002 |
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".