Additional file 2 of Comprehensive characterization of ubiquitinome of human colorectal cancer and identification of potential survival-related ubiquitination
Bibliographic record
Abstract
Additional file 2. Table S1. Ubiquitination annotation. Table S2. Protein annotation. Table S3. 42 proteins having ten or more than ten ubiquitination modifications. Table S4. 20 ubiquitin-binding motifs. Table S5. 2242 proteins with an upregulated ubiquitination and 1204 proteins with a down-regulated ubiquitination. Table S6. 1172 up-regulated proteins and 1700 down-regulated proteins. Table S7. 646 Secretory proteins. Table S8. 53 proteins having an upregulated expression simultaneously with a down-regulated ubiquitination and 116 proteins having down-regulated expression simultaneously with an up-regulated ubiquitination. Table S9. 7 proteins having an up-regulated expression simultaneously with a down-regulated ubiquitination. Table S10. 52 proteins having a down-regulated expression simultaneously with an up-regulated ubiquitination. Table S11. 101 proteins which were probably associated with the overall survival rates of CRC patients.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.218 | 0.068 |
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".