Additional file 5: Figure S4. of A novel strain of cynomolgus macaque cytomegalovirus: implications for host-virus co-evolution
Bibliographic record
Abstract
Break down of two-dimensional bit-score plots between CyCMV Mauritius-CyCMV Ottawa versus CyCMV Mauritius-RhCMV 180.92 by ORF function. Graphs represent comparisons of ORF homologue bit-scores across three strains simultaneously. ORFs are coloured according to known function. Individual ORF may have several functions and are present in multiple plots. Immune ORFs are involved in host immune regulation or evasion, entry ORFs are known cell entry factors, temperance ORFs are involved in temperance of viral growth, membrane ORFs are presented in cell membrane on infected cells or in virions, DNA/nuclear are known to interact with DNA or shuttle to the cell nucleus, capsid ORFs form the virus capsid, tegument proteins are found in the viral tegument, the function of ORFs with other known function vary, and the function is unknown at the time of writing for ORFs plotted as unknown. ORFs are annotated according to CyCMV Mauritius names except for ORFs of unknown function or membrane ORF where some ORF are left unlabelled. (PDF 50 kb)
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.880 | 0.215 |
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".