Leaching phosphorous from the lime mud of kraft pulp mills: Towards sustainability
Bibliographic record
Abstract
Abstract The optimum conditions needed to separate phosphorus from the lime mud generated in kraft pulp mills were identified using different leaching solutions including carbonate, bicarbonate, and green liquor under variety of conditions. Carbonate ions seemed to be the active ion in the phosphorus leaching process. Bicarbonate solution seems to be the most effective leaching agent by removing 84% of phosphorus under the optimum operating conditions of 95°C, 2.92 m, and solution‐to‐ mud mass ratio of 3.6. The shrinking core model was used to determine the leaching mechanism and it showed that the leaching process is controlled by a mix of chemical reaction and diffusion through the particle. Two empirical models were developed to predict the leaching efficiency as a function of carbonate concentration and temperature. Counter‐current leaching was shown to be beneficial in increasing the leaching efficiency with the carbonate solutions.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 teacher head, 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".