Inter-Laboratory Robustness of Next-Generation Bile Acid Study in Mice and Humans: International Ring Trial Involving 12 Laboratories
Bibliographic record
Abstract
BACKGROUND: The increasing relevance of individual bile acids quantification in biological samples requires analytical standardization to guarantee robustness and reliability of laboratory results. We have organized the first international ring trial, carried out in 12 laboratories, to evaluate the newly developed LC-MS/MS-based test kit for bile acid analysis. METHODS: Each laboratory received a Biocrates® Bile Acids Kit including system suitability test (SST) protocol. The kit is designed to analyze 16 individual human and 19 mouse bile acids. A set of 9 human and mouse plasma samples was measured in replicates. Laboratories were first required to pass the acceptance criteria for the SST. Within the subset of laboratories passing SST criteria, we evaluated how many laboratories met the target criteria of 80% of reported values with a relative accuracy within the 70%-130% range and analytical precisions (%CV) below 30%. RESULTS: A total of 12 of 16 participating laboratories passed the SST as the prerequisite to enter the ring trial. All 12 laboratories were then able to successfully run the kit and ring trial samples. Of the overall reported values, 94% were within 70%-130% relative accuracy range. Mean precision was 8.3% CV. The condition of CV <30% was fulfilled by 99% of the reported values. CONCLUSIONS: The first publically available interlaboratory ring trial for standardized bile acids quantification in human and mouse plasma samples showed very good analytical performance, within acceptance criteria typically applied in the preclinical environment. The kit is therefore suitable for standardized quantitative bile acid analysis and the establishment of reference values.
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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 | 0.083 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".