OECD validation study to assess intra- and inter-laboratory reproducibility of the zebrafish embryo toxicity test for acute aquatic toxicity testing
Bibliographic record
Abstract
The OECD validation study of the zebrafish embryo acute toxicity test (ZFET) for acute aquatic toxicity testing evaluated the ZFET reproducibility by testing 20 chemicals at 5 different concentrations in 3 independent runs in at least 3 laboratories. Stock solutions and test concentrations were analytically confirmed for 11 chemicals. Newly fertilised zebrafish eggs (20/concentration and control) were exposed for 96h to chemicals. Four apical endpoints were recorded daily as indicators of acute lethality: coagulation of the embryo, lack of somite formation, non-detachment of the tail bud from the yolk sac and lack of heartbeat. Results (LC50 values for 48/96h exposure) show that the ZFET is a robust method with a good intra- and inter-laboratory reproducibility (CV<30%) for most chemicals and laboratories. The reproducibility was lower (CV>30%) for some very toxic or volatile chemicals, and chemicals tested close to their limit of solubility. The ZFET is now available as OECD Test Guideline 236. Considering the high predictive capacity of the ZFET demonstrated by Belanger et al. (2013) in their retrospective analysis of acute fish toxicity and fish embryo acute toxicity data, the ZFET is ready to be considered for acute fish toxicity for regulatory purposes.
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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 | 0.029 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".