Additional file 16 of SnoRNA copy regulation affects family size, genomic location and family abundance levels
Bibliographic record
Abstract
Additional file 16: Figure S14. H/ACA snoRNA copies can be regulated in a tissue-specific manner. (A) Differential top tissue for expressed members of a same family. Local scatterplot of each family displaying the abundance of each member of the indicated H/ACA families. The color of the circles represents the tissue in which the member is most abundant. (B) The rank of abundance of members of a family can change between tissues. Categorical heatmap showing the member of highest abundance for all H/ACA families across tissues. Only families with two or more expressed members in at least one tissue are shown. Member 1 is the member with highest total abundance in all tissues, member 2 has the second highest total abundance, and so on. Families in which at least two distinct members are the most abundant in tissues are said to have a switch in the most abundant member across tissues. (C-F) Abundance patterns of family members across tissues. Bar charts displaying the abundance of all expressed (> = 1 average TPM) members across all tissues considered for a given family. Families can display consistent ranking across tissues as shown for the SNORA7 family, or switches between family members as shown for the SNORA71, SNORA14 and SNORA77 families.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.496 | 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 teacher head, 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".