Testing models of aquatic N<sub>2</sub>O flux for inland waters
Bibliographic record
Abstract
The current Intergovernmental Panel on Climate Change (IPCC) method for tabulating agricultural nitrous oxide (N2O) emissions suggests that aquatic ecosystems may be important N2O sources. However, estimates are highly uncertain, and the method to estimate emissions is rarely tested. The default IPCC emission factor for groundwater and surface drainage (EF5-g; defined as N2O-N:nitrate-N) has been lowered recently. Our data support further reduction. Notably, we present the first EF5-gdata under ice, which reflects groundwater inputs not confounded by gas exchange. These under-ice data suggest an EF5-gof 0.13%, approximately half the current IPCC default value. Our data from the open-water season also suggest a reduction to 0.11% (based on annual means). The data highlight major problems with the IPCC method. EF5-gwas extremely variable, with the highest values observed in a stream that was a net sink of N2O. Testing the overall method for freshwater emissions is more problematic because of the multidecade transit time from headwaters in our study region to the Atlantic Ocean and limited information on emissions from lakes.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".