Human-HIV1 All-to-All Inter-Species Predictions using PIPE4, SPRINT, SPPS
Bibliographic record
Abstract
All-to-all prediction scores between Human and HIV1 for three independent sequence-based PPI predictors: PIPE4, SPRINT, SPPS. Each algorithm was trained on intra-species PPIs (Human-Human & HIV1-HIV1) to generate the inter-species predictions. The training samples were obtained from BioGRID. The human proteome was obtained from Uniprot (Proteome Id: UP000005640) and filtered for Reviewed/Swiss-Prot status; resulting in 20,350 proteins (7 proteins excluded due to sequence length). The HIV1 proteome was similarly obtained (Proteome Id: UP000002241); resulting in 9 proteins. All 183,087 predictions are provided for each method except SPPS for which 25 human protein sequences were excluded for having non-standard amino acids. Each file contains three columns of comma separated values representing: human-protein,hiv1-protein,score where the score column represents the likelihood of interaction for that given PPI. Files are sorted on the Human protein and then on the HIV1 protein.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.035 |
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".