Refinements to the diastereoisomer‐specific method for the analysis of hexabromocyclododecane
Bibliographic record
Abstract
The emergence of hexabromocyclododecane (HBCD) as a bromine-based flame retardant of concern is partly attributable to recent measurements on the environmental occurrence of the individual diastereoisomers (alpha, beta and gamma). These measurements were fuelled by a newly developed liquid chromatography/tandem mass spectrometric (LC/MS/MS)-based analytical method. However, in the course of our recent studies on the environmental fate and behaviour of the diastereoisomers of HBCD, some interesting features of the LC/MS/MS method became apparent. For example, the ion signal of the native ions was found to be dependent on the final extract volume. This was true for both biotic and sediment samples and was found to arise from the suppression of the ion signal due to endogenous material in the extracts that escape clean-up. We have also found differences in the stability of the diastereoisomers in different solvents. If left unaccounted for, both factors can compromise analytical measurement data. By way of a series of controlled experiments conducted at our two laboratories [Department of Fisheries & Oceans Canada (DFO) and Environment Canada (EC)], we illustrate these features and demonstrate that use of newly synthesized labelled HBCD isomers [(13-carbon (13C) and deuterium (d18)] can minimize and often circumvent matrix-related effects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".