An Evaluation of Sources of Nitrogen in Shallow Groundwater Using <sup>15</sup>N Abundance Technique
Bibliographic record
Abstract
A (15)N abundance technique was employed to identify the source of NO(3)-N in groundwater under three commercial citrus production sites in central Florida. Water samples were collected from 0 to 300 and 300 to 600 cm depths in the surficial aquifer and analyzed for NO(3)-N and delta N-15 (delta (15)N). Groundwater samples were also collected in a residential area adjacent to one of the citrus groves and analyzed for NO(3)-N and delta (15)N. The delta (15)N values were in the range of (+)1 to (+)10% in both depths underneath the citrus groves. The range of delta (15)N measured in this study represents the range expected for groundwater that was impacted by NO(3)-N originated from mineralization of organic N from the soil as well as from the crop residue. There are occasional high delta (15)N values which are indicative of the effects of NH(3) volatilization losses of applied fertilizer N. The range of delta (15)N values for groundwater samples collected from the residential area adjacent to the citrus groves was very similar to that from the groundwater underneath the citrus groves. Thus, the source of NO(3)-N that impacted the groundwater under the citrus groves also impacted the groundwater in the adjacent residential area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".