Additional file 1 of HIV-1 subtype C Nef-mediated SERINC5 down-regulation significantly contributes to overall Nef activity
Bibliographic record
Abstract
Additional file 1. In vitro Nef functional measurements and E values of patient-derived Nef clones. Excel file showing in vitro Nef functional measurements (SERINC5 down-regulation, CD4 down-regulation, HLA-I down-regulation and alteration of TCR signalling) for Nef clones derived from individuals in early subtype C infection. Nef functions are expressed relative to SF2 Nef (where SF2 Nef function = 1). E values, which are a proxy for overall Nef function in vivo, have been predicted by computational modelling for each of these patient-derived Nef clones (17) and are shown alongside the in vitro Nef functional measurements. dE0 values were derived from the Nef fitness landscape Ising model (only the consensus amino acid present at each residue was modelled explicitly) for each Nef clone, while dE90 values were derived from the Nef fitness landscape Potts model (each amino acid present at each residue was modelled explicitly). Clinical measurements, including viral load set point (log10 copies/ml), rate of CD4+ T cell decline (cells/mm3 per month), baseline viral load (log10 copies/ml), baseline CD4+ T cell count (cells/mm3) and follow-up time (the number of days from first CD4+ T cell count to last CD4+ T cell count available) are also shown.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.865 | 0.166 |
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".