Detection and quantification of organosulfur species in the Tagish Lake Meteorite by highly sensitive <scp>LC‐MS</scp>
Bibliographic record
Abstract
Abstract We analyzed the methanol extracts of six pristine specimens of the Tagish Lake meteorite (TL1, TL4, TL5A, TL6, TL7, and TL10a) and heated and unheated samples of Allende using high‐performance liquid chromatography coupled with high‐resolution, accurate mass–mass spectrometry (HPLC‐HRAM‐MS). All samples contained ppm levels of sulfate and methyl sulfate. The most abundant organosulfur compound in the methanol extracts of the Tagish Lake and Allende samples was methyl sulfate, which was likely formed primarily via an esterification reaction between intrinsic sources of methanol and sulfate. A homologous series of polythionic acids was also observed in the extracts of the Tagish Lake specimens and Allende. The polythionic acids were the most abundant soluble inorganic sulfur species found in the meteorites. Our results were confirmed using retention time, accurate mass, isotope matching, and tandem mass spectrometry (MS/MS). Hydroxymethanesulfonic acid, previously reported in Tagish Lake, was found only in an unheated Allende sample and in low abundance. Here, we propose possible sulfate formation pathways that begin with interstellar dimethyl sulfide, dimethyl disulfide, methyl sulfide, or methanethiol via cold, nebular processes within the interstellar medium and continue via MSA as an intermediary compound ending within planetary bodies with sulfate and methyl sulfate as the final products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".