Electrospray tandem mass spectrometric measurements of organotin compounds
Bibliographic record
Abstract
Electrospray mass spectrometry of a series of organotin compounds in solutions of methanol are reported. Low energy collision‒induced dissociation MS/MS analysis of diagnostic precursor ions confirmed the characteristic fingerprint patterns obtained in the conventional electrospray spectra and proved to be a specific and very sensitive method for quantification of the (R3Sn)2O and the series of RnSnX4–n compounds in environmental matrices. Concentrations of butyltin compounds (TBTX, DBTX2 and MBTX3) in sediment reference materials PACS‐1 and PACS‐2 and butyltin and phenyltin compounds (TBTX, DBTX2, MBTX3, TPTX, DPTX2 and DPTX3) in Quasimeme II biota reference material (QSP001BT) were determined. The organotin compounds were extracted from the reference materials with 1‐butanol followed by dilution with methanol containing 1 mM ammonium acetate. The extracts were introduced directly into the electrospray source by a continuous flow of MeOH : H2O (60 :40). Quantitation of TBTX, DBTX2, TPTX, DPTX2 and DPTX3 was achieved by low energy CID tandem mass spectrometry using the Multiple Reaction Monitoring (MRM) analysis with the appropriate MS/MS transitions (positive ion electrospray ionization). Quantitation of MBTX3 was achieved using a negative ion electrospray CID tandem mass spectrometry method. For all samples quantitation was achieved by use of the method of standard addition, relative extraction recoveries were determined spiking with internal standards of mono‒, di‒ and triorganotin compounds separately to different 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".