An inter-laboratory study on the variability in measured concentrations of 17β-estradiol, testosterone, and 11-ketotestosterone in white sucker: Implications and recommendations
Bibliographic record
Abstract
Endocrine-disrupting chemicals are exogenous substances that can impact the reproduction of fish, potentially by altering circulating concentrations of 17β-estradiol (E2), testosterone (T), and 11-ketotestosterone (11-KT). Common methods to measure steroids in plasma samples include radioimmunoassays (RIAs) and enzyme-linked immunosorbant assays (ELISAs). The present study examines variability in E2, T, and 11-KT across 8 laboratories measuring reference and pulp mill effluent-exposed white sucker (Catostomus commersoni) plasma. We examine the contribution of assay type (RIA vs ELISA), standardized hormone extraction, location of values on the standard curve (upper and lower limits), and other variables on the ability to distinguish hormone levels between reference and exposed fish and the impact of these variables on quantitation of hormones in different laboratories. Of the 8 participating laboratories, 7 of 8 and 7 of 7 identified differences between sites for female E2 and female T, respectively, and 7 of 7 and 4 of 5 identified no differences between male T and male 11-KT. Notably, however, the ng/mL concentration of steroids measured across laboratories varied by factors of 10-, 6-, 14-, and 10-fold, respectively. Within laboratory intra-assay variability was generally acceptable and below 15%. Factors contributing to interlaboratory variability included calculation errors, assay type, and methodology. Based on the interlaboratory variability detected, we provide guidelines and recommendations to improve the accuracy and precision of steroid measurements in fish ecotoxicology studies.
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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 | 0.043 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".