Bibliographic record
Abstract
TO THE EDITOR—I thank Dr Andi Shane for the overall positive comments concerning my editorial [1], which examined consumer interest in raw milk in the context of a serious Escherichia coli O157 outbreak linked to consumption of raw cow's milk [2, 3]. Shane takes issue with my use of the term “probiotic” and points out correctly that raw milk does not meet the current definition of a probiotic. While I agree wholeheartedly with this assessment of the terminology, it is worth noting that the original sentence read “perceived probiotics” and referred to consumer perception rather than scientific definition. However, the letter provides an opportunity to highlight some misconceptions held by raw milk proponents relating to health benefits and beneficial bacteria. Raw milk consumption among farm families is common as a result of convenience and cultural norms [4]. It is perhaps less clear why some urban and suburban consumers are choosing a product that has been deemed hazardous by the medical and public health communities. The patients described in the study by Guh et al fit the latter demographic and purchased legal, commercial raw milk from the farm or a retail store [3]. Potter et al provided early insight into the health benefit claims made by raw milk proponents, suggesting that these claims were an important reason for consumer interest in raw milk as a health food [5]. A subsequent survey of California raw milk drinkers in the 1990s reported “health benefits” and “taste” as the leading reasons why respondents chose raw milk [6]. In a recent small survey from Wisconsin, the majority of respondents called raw milk a “living food,” saying “it contains beneficial probiotics and enzymes that are especially helpful for digestion” [7].
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 | 0.009 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.054 | 0.066 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".