Cation Exchange Capacity and Base Saturation of 64 Peat Mosses
Bibliographic record
Abstract
Problems of inconsistent initial pH in peat moss-based substrates that are created using standard formulas for limestone additions, and pH drift from the target in those substrates may be due to variations in the CEC and BS of peat moss. This study was conducted to determine whether such variation exists. Sixty-four peat moss samples were obtained from several bogs across Alberta, Canada. Adsorbed cations on each peat moss sample were displaced with hydrochloric acid (HCl), and flushed out with three deionized water washes. The displacing/flushing solution was collected and later analyzed for concentration of bases (Ca, Mg, K, and Na) using atomic absorption spectrometry. After cations were removed, the peat moss exchange sites were saturated with barium acetate [Ba(OAc) 2 ] to displace the H + , which were then collected by a second flushing with deionized water. This second displacing/flushing solution was titrated with measured amounts of NaOH to a phenolphthalein end point. Base saturation and CEC were calculated. There were significant variations in CEC (ranging from 108.12 to 162.25 cmol·kg -1 ) and BS (ranging from 13.52% to 63.97% of CEC) among the peat moss samples. Ca accounted for 78.08% of the BS. For a given peat moss, the higher the BS, the lower the neutralization requirement to achieve a target pH. Also, high CEC peat mosses may have greater buffering capacity than those with low CEC, which may result in less pH drift.
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.
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".