Unique Solid Phase Microextraction Sampler Reveals Distinctive Biogeochemical Profiles among Various Deep-Sea Hydrothermal Vents
Bibliographic record
Abstract
Current methods for biochemical and biogeochemical analysis of the deep-sea hydrothermal vent ecosystems rely on water sample recovery, or in situ analysis using underwater instruments with limited range of analyte detection and limited sensitivity. Even in cases where large quantities of sample are recovered, labile dissolved organic compounds may not be detected due to time delays between sampling and preservation. Here, we present a novel approach for in situ extraction of organic compounds from hydrothermal vent fluids through a unique solid phase microextraction (SPME) sampler. These samplers were deployed to sample effluent of vents on sulphide chimneys, located on Axial Seamount in the North-East Pacific, in the Urashima field on the southern Mariana back-arc, and at the Hafa Adai site in the central Mariana back-arc. Among the compounds that were extracted, a wide range of unique organic compounds, including labile dissolved organic sulfur compounds, were detected through high-resolution LC-MS/MS, among which were biomarkers of anammox bacteria, fungi, and lower animals. This report is the first to show that SPME can contribute to a broader understanding of deep sea ecology and biogeochemical cycles in hydrothermal vent ecosystems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".