Dufour et al. Source Data.xlsx
Bibliographic record
Abstract
Dataset used to create every graph of the paper "Phenotypic characterization of single CD4+ T cells harboring genetically intact and inducible HIV genomes" in Nature Communications <br> Author list: Caroline Dufour<sup>1</sup>, Corentin Richard<sup>1</sup>, Marion Pardons<sup>1</sup>, Marta Massanella<sup>1</sup>, Antoine Ackaoui<sup>1</sup>, Ben Murrell<sup>2</sup>, Bertrand Routy<sup>1</sup>, Réjean Thomas<sup>3</sup>, Jean-Pierre Routy<sup>4</sup>, Rémi Fromentin<sup>1</sup>, Nicolas Chomont<sup>1</sup> <br> <sup>1</sup>Centre de Recherche du CHUM and Department of Microbiology, Infectiology and Immunology, Université de Montréal, Montreal, H2X 0A9, Quebec, Canada <sup>2</sup>Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 171 77, Sweden <sup>3</sup>Clinique médicale l’Actuel, Montreal, H2L 4P9, Quebec, Canada <sup>4</sup>Division of Hematology & Chronic Viral Illness Service, McGill University Heath Centre, Montreal, H4A 3J1, Quebec, Canada
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.013 |
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; both teacher heads 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".