Tribute to Mark Wainberg
Bibliographic record
Abstract
As you will read below, most of his colleagues and former trainees wanted share personal memories of Mark intertwined with his research accomplishments and impact on HIV/AIDS treatment and care.Many of us forget Dr. Wainberg's many contribution to research because Mark did not live in the past and was always looking forward to a new drug, a new resistance pathway, and new possibilities for treatment.Many of us including myself fall victim of framing a question at a conference by discussing "our" past publication or data.Mark was never going to lecture you on his contribution to AZT resistance [1-3], discovery of 3TC inhibition and resistance [4-6], characterization of early events of reverse transcription [7, 8], description of early Vpu activity and CD4 downmodulation [9-12], the low fidelity/fitness of 3TC resistant virus [13-18], or description of alternative drug resistance pathways in non-subtype B HIV [19-21] (50+ articles).
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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.028 |
| Insufficient payload (model declined to judge) | 0.032 | 0.028 |
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".