APPLICATION OF CLEANUP METHOD OF POLYBROMINATED DIPHENYL ETHERS IN FISH TISSUE BY FREEZING -LIPID FILTRATION
Bibliographic record
Abstract
[Background] Polybrominated diphenyl ethers(PBDEs) are a group of brominated flame retardants(BFRs), which have been manufactured in large quantities and widely used in a variety of consumer goods. PBDEs in biological samples are largely associated with the lipid fraction. [Purpose] It is to apply the new method of freezing lipid filtration for the congenerspecific determination of 7 different PBDEs, 2,4,4`-TrBDE, 2,2`,4,4`-TeBDE, 2,2`,4,4`,5- PeBDE, 2,2`,4,4`,6-PeBDE, 2,2`,4,4`,5,5`-HeBDE, 2,2`,4,4`,5,6`-HeBDE, and 2,2`,3,4,4`,5`,6- HpBDE for the monitoring of biological samples. [Method] The reference fish tissue for organic contaminant analysis (WMF-01, Wellington Laboratories Inc. Ontario, Canada) was purchased. Extraction was carried out by sonication for 10 min with 100 mL of n-hexane two times. For the elimination of lipids, freezing-lipid filtration and sulfuric acid treatment were applied. [Result] A new cleanup method by freezing-lipid filtration was performed to compare with traditional sample pretreatment such as EPA official method. The sulfuric acid treatment of extracts from 10 g fish sample was require a lot of time and toxic chemical for phase separation. For comparison of method performance, The concentrations obtained by freezing-lipid filtration were almost equivalent to sulfuric acid cleanup. Compared with other cleanup methods for lipid elimination from biological samples, analytical results obtained by freezing-lipid filtration were almost equivalent to those by other official methods. This method can be applied as rapid screening tool for the determination of PBDEs in biological samples.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".