Determining mRNA half-lives on a transcriptome-wide scale
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Every step in the life cycle of an RNA transcript provides opportunity for regulation. One important aspect of post-transcriptional control is the regulation of RNA stability. Of the many strategies for determining mRNA stability, transcription inhibition and metabolic labeling have proved the most amenable to high-throughput analysis and have opened the door to dissecting mRNA decay transcriptome-wide. Here, we describe experimental and computational methods to determine transcriptome-wide RNA stabilities using both pharmacological inhibition of transcription and metabolic labeling. To aid in the analysis of these experiments, we discuss key characteristics of high-quality experiments and address other experimental and computational considerations for the analysis of mRNA stability. Broader application of these approaches will further our understanding of mRNA decay and illuminate its contribution to different biological processes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it