Paraben Levels in an Urban Community of Western Canada
Bibliographic record
Abstract
With effective antibacterial and antifungal properties, commercially used parabens are synthetic compounds widely utilized as preservatives in cosmetics, personal care products, pharmaceuticals, and as an additive in some foodstuffs. While long regarded as relatively safe and nontoxic, recent research has demonstrated xenoestrogenic properties of anthropogenic parabens with early evidence that paraben exposure may be linked to breast cancer, thyroid dysfunction, allergy, and obesity. In an attempt to determine the prevalence of paraben exposure in a Canadian urban community, a sample of convenience was done by measuring urinary levels of methyl, ethyl, propyl, butyl, and isobutyl parabens (MP, EP, PP, BP, and IP) in 39 consecutive patients in an Alberta primary care clinic. In 28 female patients including 9 pregnant women, the median urinary levels (in μ g/L) were 25.45 for MP, 10.17 for EP, 2.80 for PP, 0.30 for BP, and 0.24 for IP. In 11 male patients, the median urinary levels (in μ g/L) were 25.95 for MP, 10.37 for EP, 3.09 for PP, 0.35 for BP, and 0.22 for IP. Especially high urinary paraben levels were reported in a few patients, with the highest urinary concentrations (in μ g/L) reported as 966.46 for MP, 220.6 as EP, and 612.73 for PP. It is evident that exposure to assorted parabens is a routine event for many if not most individuals, including pregnant women, in urban Alberta, Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".