Bibliographic record
Abstract
Research for a dissolved nitrogen budget was conducted at Mer Bleue bog near Ottawa, ON, from May 20, 2003 to May 21, 2004. Mer Bleue is located within an area experiencing the highest levels of atmospheric nitrogen deposition in North America, although these levels are only low to moderate compared to those in Europe. Continuous measurements of precipitation, evapotranspiration, bog water table level and outflow water depth were used in conjunction with discrete measurements of precipitation and outflow to determine the hydrologic budget. Water samples were taken from precipitation collectors, piezometers at various depths and locations throughout the bog, and an outflow point in order to gauge changes and patterns in chemical concentrations at various points throughout the bog. The nature of the bog morphology and landscape allowed for collection of water samples from a single outflow point. Chemical analysis combined with the water budget revealed that the majority of the dissolved nitrogen is entering the bog as NO3-N and NH 4-N (inorganic nitrogen), and leaving the bog as dissolved organic nitrogen (DON). Export of nitrogen was generally low relative to the input, and was only a very small fraction of the huge amount of nitrogen stored in the bog. Bog porewater concentrations were dominated by DON and did not show spatial patterns in relation to the bog edge. When comparing the annual accretion of nitrogen at the bog to the long-term storage numbers, it was apparent that there is a missing source of nitrogen. From the literature and patterns in the bog, it appears that this missing input at Mer Bleue is likely due to a combination of previously unmeasured nitrogen fixation and more diverse usage of DON by bog vegetation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".