Versatile inlet system for on‐line compound‐specific δD and δ <sup>13</sup> C gas chromatography–oxidation/reduction–isotope ratio mass spectrometry analysis of gaseous mixtures
Bibliographic record
Abstract
Compound-specific deltaD and delta13C analyses of gas mixtures are useful indicators of geochemical and environmental factors. However, the relative concentrations of individual components in gas mixtures (e.g., H2, CO2, methane, ethane, propane, i-butane, n-butane) may vary over several orders of magnitude. The determination of hydrogen and carbon compound-specific stable isotope ratios requires that the hydrogen and carbon dioxide produced from each separated component has a concentration adjusted to match the dynamic range of the stable isotope mass spectrometer. We present a custom-built gas sampling and injection system (GASIS) linked with a Delta Plus XP mass spectrometer that provides flexibility, ease of operation, and economical use of small gas samples with wide ranges of analyte concentrations. The overall on-line GC-ox/red-IRMS (Gas Chromatography - oxidation/reduction - Isotope Ratio Mass Spectrometry) system consists of (i) a customized GASIS inlet system and (ii) two alternative reactors, namely an oxidative Cu-Ni-Pt reactor at 950 degrees C for production of CO2 and a reductive graphitized Al2O3 reactor at 1420 degrees C for production of H2. In addition, the system is equipped with (iii) a liquid nitrogen spray-cooling unit for cryo-GC-focusing at -20 degrees C, and (iv) a Nafion dryer for removal of water vapor from product CO2. The three injection loops of the GASIS inlet allow flexibility in the volume of injected analyte gas (e.g., from 0.06 to 500 microL) in order to measure reproducible deltaD and delta13C values for gases at concentrations ranging from 100% down to 10 ppm. We calibrate our GC-ox/red-IRMS system with two isotopically distinct methane references gases that are combusted off-line and characterized using dual-inlet IRMS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".