Bibliographic record
Abstract
The most important factor affecting the oocyte and early embryo transcriptome is the legacy from the follicular environment prior to meiotic resumption. Up to the 8-cell stage, the oocyte responds to maternal instructions stored before resumption of the meiotic division. Recent evidence suggests that properly prepared or programmed oocytes (in vivo) can achieve close to 100% blastocyst rates in standard in vitro conditions/media. Therefore, the optimal oocyte requires perfect follicular timing and differentiation, but the intra-oocyte mechanisms involved in such preparation are not completely understood. In addition, the influence of maternal mRNA storage and degradation, as well as the length of the poly A tail that influences the general pattern of the oocyte/early embryo transcriptome, is an important factor. Several hypotheses have been put forth to explain the depletion of the maternal store, including the potential role of microRNA (miRNA) in this process. The activation of the embryonic genome could be dependent on, or associated with, the process of maternal mRNA degradation, but obviously other functions are being activated at this critical time point. This review will focus on the period from full-size oocytes to the eight-cell stage and will summarize the impact of the important factors, that is, follicle, maternal RNA storage and embryonic genome activation, on the transcriptome.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".