Phosphorus forms by depth in sediments from the Qu’Appelle lakes, Saskatchewan, Canada
Bibliographic record
Abstract
Understanding sediment phosphorus (P) compounds is essential to managing P in lake sediments because P speciation will determine bioavailability and reactivity. Little is known about organic P (Po) in hardwater eutrophic lakes in the North American Great Plains, or the role of metals in Po cycling. Sediment cores (0–12 cm deep) collected from four lakes from the Qu’Appelle chain in Saskatchewan, Canada, were sectioned by depth and analyzed by solution P nuclear magnetic resonance spectroscopy to characterize P forms. Concentrations and pools of calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), and aluminum (Al) were also determined. A range of P compounds was detected with significant interactions between lakes and depth for orthophosphate, phytate and DNA, and significant differences among lakes or with depth for polyphosphates and phosphonates. The main class of Po compounds identified in all lakes was orthophosphate diesters, including phospholipids and DNA, typical of living biota, suggesting that P immobilized by microbes and algae is an important pool in the sediments of these lakes. There were significant differences in metal concentrations among the lakes. In three lakes, Ca concentrations were high, and P was tightly bound with Ca compounds of low solubility. In the fourth lake with lower Ca concentrations, P appeared to be loosely bound to Al and Fe compounds. Our study indicates that there were significant differences in P compounds and the factors controlling their cycling among these four lakes in the same chain, which has implications for P management and water quality control.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".