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
Splicing of precursor messenger RNA (pre‐ mRNA ) removes the intervening sequences (introns) and joins the expressed regions (exons) in the nucleus, before an intron‐containing eukaryotic mRNA transcript can be exported and translated into proteins in the cytoplasm. While some sequences are always included or excluded (constitutive splicing), others can be selectively used (alternative splicing) in this process. Particularly by alternative splicing, up to tens of thousands of variant transcripts can be produced from a single gene, which contributes greatly to the proteomic diversity for such complex cellular functions as ‘wiring’ neurons in the nervous system. Disruption of this process leads to aberrant splicing, which accounts for the defects of up to 50% of mutations that cause certain human genetic diseases. In this review, we describe the different mechanisms of aberrant splicing that cause or have been associated with neurological diseases. WIREs RNA 2013, 4:631–649. doi: 10.1002/wrna.1184 This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it