Salicylate Method for Ammonia Quantification in Nitrogen Electroreduction Experiments: The Correction of Iron III Interference
Bibliographic record
Abstract
The salicylate method is one of the ammonia quantification methods that has been extensively used in literature for quantifying ammonia in the emerging field of nitrogen (electro)fixation. The presence of iron in the sample causes a strong negative interference on the salicylate method. Today, the recommended method to deal with such interferences is the experimental correction method: the iron concentration in the sample is measured using an iron quantification method, and then the corresponding amount of iron is added to the calibration samples. The limitation of this method is that when a batch of samples presents a great iron concentration variability, a different calibration curve has to be obtained for each sample. In this work, the interference of iron III on the salicylate method was experimentally quantified, and a model was proposed to capture the effect of iron III interference on the ammonia quantification result. This model can be used to correct the iron III interferences on ammonia quantification. The great advantage of this correction method is that it only requires three experimental curves in order to correct the iron III interference in any sample provided the iron III concentration is below the total peak suppression concentration.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".