Additional file 3 of Integrated small RNA, mRNA and protein omics reveal a miRNA network orchestrating metabolic maturation of the developing human heart
Bibliographic record
Abstract
Additional file 3: Fig. S1A-G. Significant differentially expressed genes across gestational age (P value < 0.05) of each small RNA population. Table S1-6. Functional enrichment analysis of miRNAs clustered in each of six clusters of expression pattern. Fig. S2. Gene ontology terms (biological functions) and functional annotations (KW) enriched amongst genes upregulated (A) and downregulated (B) in fetal hearts across gestation. Fig. S3. (A) Analysis pipeline used to correlate miRNA expression data to mRNA expression data. (B, C) Functional enrichment analysis of differentially expressed miRNA-mRNA targets. Fig. S4A, B. Functional enrichment analysis of top 5% downregulated miRNA-mRNA targets. Fig. S5. Significant differentially expressed proteins between 10- and 18-weeks fetal hearts (P value < 0.05). Fig. S6. Controls for reporter metabolite analysis.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.799 | 0.151 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".