Automated quantitative and isotopic ( <sup>13</sup> C) analysis of dissolved inorganic carbon and dissolved organic carbon in continuous‐flow using a total organic carbon analyser
Bibliographic record
Abstract
A method for the automated (13)C analysis of dissolved inorganic and organic carbon species has been developed to operate on a continuous-flow isotope ratio mass spectrometer (CF-IRMS). For natural and anthropogenic carbon species, the (13)C stable isotope has proven to be an excellent environmental tracer. Analytical performance tests were carried out on various organic compounds from easily oxidisable (sugar) to difficult (humic acid). A set of natural samples was also analysed to confirm the flexibility of the system. Analytical precision (2sigma) is typically <0.20 per thousand with sample reproducibility from 0.10-0.35 per thousand depending on reactivity of material. We believe this to be the first successful use of a total organic carbon (TOC) analyser for both dissolved inorganic and, specifically, dissolved organic species for (13)C stable isotope analysis in an automated CF-IRMS system. Routine analysis is achieved fairly quickly, is relatively simple with little or no sample manipulation, and will allow new and exciting studies for stable isotope research in both natural abundance and organic tracer studies not easily achieved before.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".