Probing microRNAs with microarrays: Tissue specificity and functional inference
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
MicroRNAs (miRNAs) are short, stable, noncoding RNAs involved in post-transcriptional gene silencing via hybridization to mRNA. Few have been thoroughly characterized in any species. Here, we describe a method to detect miRNAs using micro-arrays, in which the miRNAs are directly hybridized to the array. We used this method to analyze miRNA expression across 17 mouse organs and tissues. More than half of the 78 miRNAs detected were expressed in specific adult tissues, suggesting that miRNAs have widespread regulatory roles in adults. By comparing miRNA levels to mRNA levels determined in a parallel microarray analysis of the same tissues, we found that the expression of target mRNAs predicted on the basis of sequence complementarity is unrelated to the tissues in which the corresponding miRNA is expressed.
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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 | 0.000 | 0.000 |
| 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