20 años no es nada: conocimiento científico, producción de medicamentos y necesidades sociales.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alkaline residuals, such as wood ash and lime mud generated from pulp and paper mills, could be recycled as liming agents in sugar maple (Acer saccharum Marsh.) forests affected by soil acidification. The objectives of this study were (1) to evaluate soil chemistry, in particular soil acidity, after the application of three alkaline residuals from the pulp and paper industry, and (2) to determine if these alkaline residuals altered soil greenhouse gas (GHG) emissions as a result of the change in soil pH or due to their chemical composition. Soil properties and GHG fluxes were monitored for two years after alkaline residuals were applied to six forest sites dominated by sugar maple in southeastern Quebec, Canada. Each site received six treatments: wood ash applied at 5, 10 and 20 t ha<sup>-1</sup>, lime mud (7.5 t ha<sup>-1</sup>), a mixture of slaker grits and green liquor sludge (7 t ha<sup>-1</sup>) and an unamended control. These treatments had acid-neutralizing power from 0 to 9 t ha<sup>-1</sup>. All alkaline residuals buffered soil acidity as a function of their neutralizing power, and more neutralization occurred in the forest floor layer than in the underlying mineral soil. In the forest floor, the alkaline residual treatments significantly increased pH by more than one unit, nearly doubled the base saturation, and reduced exchangeable acidity, Al and Fe concentrations compared to control plots. The CO<sub>2</sub> and N<sub>2</sub>O fluxes were lower after application of alkaline residuals, and this was related to the soil pH increase and the type of alkaline residual applied. Lime mud was more effective at reducing GHG fluxes than other alkaline residuals. We conclude that these alkaline residuals can effectively counteract soil acidity in sugar maple forests without increasing soil GHG emissions, at least in the short term.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it