Differentiation of (Mixed) Halogenated Dibenzo-<i>p</i>-Dioxins by Negative Ion Atmospheric Pressure Chemical Ionization
Bibliographic record
Abstract
Brominated and mixed halogenated dibenzo-p-dioxins (PBDDs and PXDDs) may well be as toxic as 2,3,7,8-tetrachloro-dibenzo-p-dioxin (2378-TCDD), a compound reputed as one of the most toxic chemicals known to exist. However, studies on the occurrence of PXDDs have been hampered by a lack of authentic standards as well as separation techniques capable of resolving the enormous number of potential isomers. Electron ionization (EI) mass spectrometry based methods are of limited value due to the lack of isomer specific fragmentation. Negative ion atmospheric pressure chemical ionization (APCI(-)) of 2378-TCDD was described in this journal over 30 years ago. Under these conditions, the reaction between O2(-•) and 2378-TCDD results in structure diagnostic cleavages of the C-O bonds, which can distinguish TCDD isomers on the basis of Cl distribution between the two aromatic rings. In the present study, the analogous ether cleavages of PBDDs and PXDDs were studied using a gas chromatograph-quadrupole time-of-flight (GC-QTOF) mass spectrometer coupled using APCI. The results indicate comparable detection limits for the radical cations [M(•+)] and negative pseudomolecular ions [M-Cl+O](-): approximately 5 fg and 10 fg, respectively, for 2378-TCDD and 5-10 fg and 10-30 fg, respectively, for the 2,3,7,8-substituted PXDDs. Detection limits obtained by monitoring the ether cleavage products were somewhat higher (between 100 and 600 fg) but still acceptable for trace analysis of PXDDs. Such reactions may resolve coeluting isomers, which is crucial for the identification of PXDDs. The technique is demonstrated by differentiating PXDD isomer classes in a sample obtained from a major industrial fire that would not be feasible using EI or positive ion APCI(+).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".