Fact or fiction: What is in your 15N2 and 15NH3 cylinders for sustainable ammonia and urea research?
Bibliographic record
Abstract
Attaining reliable performance indicators via 15 N-labeling is a daunting research endeavor for sustainable ammonia and urea synthesis processes, as currently obtained reaction rates and yields are often low. However, artifact and misinterpretation can be induced by ppm-level impurities in commercial 15 N 2 and 15 NH 3 cylinders, which are not well understood. Here, we report quantitative in-line gas chromatography-mass spectrometry (GC-MS) analysis of impurities in commercial 15 N 2 and 15 NH 3 cylinders at ppm level, in conjunction with 1 H-NMR methods, exemplified by 808–16,252 ppm of 14 N 15 N, 0–4,891 ppm 15 NH 3 , 3–319 ppm 14 NH 3 , 0–231 ppm of 14 NO 2 , 0–176 ppm 15 NO 2 , and 0–566 ppm 15 N 16 O impurities, some of which were not reported in cylinder certification nor previous studies. The collected results have formed recommended protocols applicable to all future 15 N labeling experiments intended to eliminate false positives.
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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 | 0.000 | 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 | 0.001 |
| 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".