Professor Mark Wainberg
Bibliographic record
Abstract
When Kuan-Teh Jeang (‘Teh’ to everyone) made the bold and prescient decision to join the earliest wave of pure online academic publishing and founded the journal Retrovirology, Mark Wainberg was one of the simplest and most obvious choices for him to invite to join the editorial team. Mark’s long established and highly respected position in the field of HIV and AIDS research added enormously to the embryonic journal’s immediate credibility and stature. Mark’s seminal achievements in recent years have been in antiretroviral therapy and viral resistance mechanisms but, in a publishing career on HIV spanning 30 years and over 550 publications, there were few areas of HIV research that he did not investigate and he brought that enormous range of expertise and experience to Retrovirology. His many achievements in the field will be described in detail by others, including his trainees and colleagues from Canada, in a shortly to be published obituary in this journal. When Teh himself was so sadly taken from us it was again Mark’s stature and reputation and his boundless enthusiasm and energy that was so important in maintaining the momentum and profile of the Journal as he took on the role of Co-Editor in Chief.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.022 |
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".