Evaluation of multiple alternative instrument platforms for targeted and non‐targeted dioxin and furan analysis
Bibliographic record
Abstract
The use of gas chromatography coupled to high-resolution magnetic sector mass spectrometers (GC-HRMS) is well established for dioxin and furan analysis. However, the use of gas chromatography coupled to triple quadrupole (MS/MS) and time of flight (TOF) mass spectrometers with atmospheric pressure ionization (API) and traditional electron ionization (EI) for dioxin and furan analysis is emerging as a viable alternative to GC-HRMS screening. These instruments offer greater versatility in the lab for a wider range of compound identification and quantification as well as improved ease of operation. The instruments utilized in this study included 2 API-MS/MS, 1 traditional EI-MS/MS, an API-quadrupole time of flight mass spectrometer (API-QTOF), and a EI-high-resolution TOF (EI-HRTOF). This study compared these 5 instruments to a GC-HRMS using method detection limit (MDLs) samples for dioxin and furan analysis. Each instrument demonstrated acceptable MDL values for the 17 chlorinated dioxin and furans studied. The API-MS/MS instruments provide the greatest overall improvement in MDL value over the GC-HRMS with a 1.5 to 2-fold improvement. The API-QTOF and EI-TOF demonstrate slight increases in MDL value as compared with the GC-HRMS with a 1.5-fold increase. The 5 instruments studied all demonstrate acceptable MDL values with no MDL for a single congener greater than 5 times that for the GC-HRMS. All 5 instruments offer a viable alternative to GC-HRMS for the analysis of dioxins and furans and should be considered when developing new validated methodologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".