History and results of the two inter‐laboratory round robin endotoxin assay studies on cotton dust
Bibliographic record
Abstract
BACKGROUND: In the US cotton industry, airborne cotton dust levels are regulated, and other countries are moving to specify safety limits for airborne endotoxins. There is concern about potential respiratory health hazards associated with agricultural and other organic dusts. In laboratories, ranking which samples have high and low levels of endotoxin is usually in good agreement between laboratories. When different laboratories assay identical samples, the levels differ. The objective of this research was to evaluate the intra- and inter-laboratory variability for 13 laboratories measuring endotoxin in cotton dust. METHOD: Two inter-laboratory round robin endotoxin assay studies were conducted using cotton dust. In the first round robin, each laboratory used their normal in-house assay method and then used a common extraction protocol. In the second round robin, a common extraction protocol and endotoxin assay kit was used. RESULTS: The intra-laboratory results had small variations but inter-laboratory results had very high variations. The inter-laboratory results using a common extraction protocol showed reduced differences. Using the same extraction protocol and endotoxin assay kit, the intra-laboratory variation was small and inter-laboratory variation was reduced but not enough for inter-laboratory agreement. Most of the laboratories were able to discern between the high and low endotoxin concentration dusts. CONCLUSIONS: Standardization has reduced the differences in results between laboratories and possibly further standardization may bring closer inter-laboratory agreement.
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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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".