Mitigating nitrous oxide emissions using nitrification and urease inhibitors in corn-based rotations following cover crops termination
Bibliographic record
Abstract
Cover crops can reduce nitrous oxide (N2O) emissions during the non-growing season and nitrification and urease inhibitors (NUIs) can reduce emissions during the growing season, but these practices have yet to be studied in tandem. The objectives of this study were to 1) quantify N2O emissions from fields under conventional (CONV) and diverse (DIV) rotation over two years and 2) determine the impact of NUIs in both rotations after corn fertilization. The flux-gradient method was deployed in four 4-ha fields using a tunable diode laser trace gas analyzer. The nitrogen use efficiency (NUE) of corn was higher in DIV fields. Compared to the CONV field, the DIV field emitted 9% more N2O, due to higher emissions after the application of fertilizer to corn. The emissions during the 3-week period post fertilizer application to corn accounted for 20-25% of total N2O emissions over two years.
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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 | 0.000 | 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 | 0.000 |
| 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 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".