Dissolved gas measurements in oceanic waters made by membrane inlet mass spectrometry
Bibliographic record
Abstract
A method is presented for the shipboard analysis of dissolved gases (O2, CO2, Ar, N2, H2S, dimethylsulfide) in oceanic waters using membrane inlet mass spectrometry (MIMS). Gases are extracted from seawater across a semipermeable membrane into the ion source of the mass spectrometer. The method can be used to simultaneously measure both major and trace gases in seawater samples in near real-time. In the case of DMS, low nmol L−1 detection limits can be achieved without any concentration step. Multiple calibration and method comparison exercises conducted in the subarctic Pacific Ocean show that the MIMS method provides gas measurements that are consistent with those obtained by standard techniques, with precision of replicate samples ranging from less than 1% to approximately 5% coefficient of variation (CV). To illustrate the usefulness of the MIMS approach, depth profiles are presented for O2, CO2, N2, and DMS at various coastal and open ocean stations in the subarctic Pacific. In addition to these discrete gas measurements, the MIMS system has also been used to continuously monitor gas concentrations along underway transects. High frequency gas measurements of O2, CO2, and DMS made along two coastal transects reveal a high degree of spatial and temporal variability in gas concentrations, likely resulting from the interplay of various biological, chemical, and physical forcings. The underway MIMS data provide insight into the biogeochemical controls on gas cycling in dynamic marine waters.
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 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".