Impact of the process of isolating humic acids from peat on their propertiesA paper submitted to the Journal of Environmental Engineering and Science.
Bibliographic record
Abstract
Humic substances (HS) can be isolated in preparative quantities from low rank coal, peat, and soil. Traditionally, treatment with solutions of NaOH, KOH, or metal salts (K 4 P 2 O 7 ) has been used for their isolation. The aim of this article is to study the effectiveness of different technologies in extracting HS from peat as well as the impact of the different extractive technologies on the properties of the isolated HS. Yields of HS depend very much on the extraction process (extractant, temperature, pretreatment procedures, solvent, mixing intensity); however, the properties of the substances obtained (molecular mass, number of functional groups, spectral characteristics) differ significantly. Yields of HS can be associated with the degree of destruction of the peat fibres and intensive destruction technologies provide opportunities to obtain HS from peat in higher yields than traditional extraction methods. However, during the extraction process, significant degradation of the humic molecules takes place.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".