Long‐term effects of successive Ca(OH)<sub>2</sub> and CaCO<sub>3</sub> treatments on the water quality of two eutrophic hardwater lakes
Bibliographic record
Abstract
1. Whole‐lake experiments were conducted in two hardwater lakes (Halfmoon and Figure Eight) in Alberta, Canada, to investigate the effectiveness of repeated lime (slaked lime: Ca(OH)2 and/or calcite: CaCO3) treatments (5–78 mg L–1) for up to 7 years. 2. Randomized intervention analysis of intersystem differences between the experimental and three reference lakes demonstrated a decline in euphotic total phosphorus and chlorophyll a concentrations in the experimental lakes after repeated lime treatments. 3. After the second lime application to Halfmoon Lake, mean winter total phosphorus release rates (TPRR) decreased to < 1 mg m–2 day–1 compared with 3.6 mg m–2 day–1 during the winter after initial treatment. In the final year of lime application, mean summer TPRR decreased to 4.5 mg m–2 day–1 compared with 7.6 mg m–2 day–1 in the pre‐treatment year. 4. Mean macrophyte biomass declined and species composition was altered at 1 and 2 m depths in Figure Eight Lake during lime application. Over the first 6 years of treatment, macrophyte biomass at 2 m declined by 95% compared with concentrations recorded during the initial treatment year. In the last year of the study, macrophyte biomass at 2 m reached initial treatment concentrations, which coincided with the greatest water transparency. Over the treatment period, macrophyte species shifted from floating to rooted plants. 5. Multiple lime applications can improve water quality in eutrophic hardwater lakes for periods of up to 7 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".