The correlations of the function and positional distribution of the <i>cis</i>-elements CArG around the TSS in the genes of <i>Mus musculus</i>
Bibliographic record
Abstract
While many studies of cis-elements CArG bound by serum response factor (SRF) are in progress, little is known about the positional distribution of the functional CArG elements around the transcription start site (TSS) of genes that they influence. We use a validated CArG data set to calculate the distance distribution of functional CArG elements around the TSS. Distances between adjacent CArGs were also analyzed. We compare these distributions with those derived using a control set of randomly selected CArGs (that were not experimentally validated for function). Our results show that most functional CArG elements (108 of 152, 71%) exist upstream of the annotated TSS, with copy number increasing as one moves closer to the TSS. Moreover, the average number of the CArG elements in the CArG-containing genes is significantly more than that in the control genes. Our study extends earlier bioinformatic analyses of functional CArG elements and provides an application of comparative sequence data to the identification of transcription factor binding sites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".