Bibliographic record
Abstract
To the Editors: Drs. Friedman, Oestreicher, Chan and their associates, in reviewing the possible link between antibiotics and breast cancer, have noted their “review suggested that acne and/or rosacea could be the underlying factor” linking the two disorders (1).At a recent Harvard and McGill–sponsored symposium entitled “Milk, Hormones and Human Health,” the link between hormones in milk and the triad of acne vulgaris, breast cancer, and prostate cancer (all hormone-responsive tissues) was seen to be gradually strengthening.11Pollak M. Milk, hormones, and human health. Oct 23-25, 2006, Boston, Massachusetts. Proceedings of the Workshop. In preparation. With this as background, it is noted that although “hormone use was taken into account” in this study, the hormones present in dairy products consumed were not part of that assessment. This is understandable, with the recent link in the dermatology literature between acne and dairy consumption having been only recently published (2-4).Whereas no data have yet been published to link acne rosacea and dairy, the subject is being actively considered and Friedman et al. provide data from the first large population to suggest this intriguing possibility.Further work in this field must consider intake of dairy hormones as the most likely source of the “uncontrolled confounding” the authors cite. Indeed, what is seen as uncontrolled confounding by Friedman et al. may be, in effect, indirect confirmation of the postulated androgenic hormonal link between acne, breast cancer, and dairy product consumption.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".