Cation Exchange Capacity and Base Saturation Variation among Alberta, Canada, Moss Peats
Bibliographic record
Abstract
Variations in moss peat cation exchange capacity (CEC) and base saturation (BS) can result in inconsistent initial pH in moss peat-based substrates created using standard formulas for limestone additions and can lead to subsequent drift from the initial pH in those substrates. This study was conducted to determine the extent of such variation. CEC and BS were measured in three replications on 64 moss peat samples that were selected from three mires across Alberta, Canada, to represent maximum gradients in plant species composition within six degrees of decomposition acceptable for professional peat-based substrates. CEC ranged from 108 to 162 cmol·kg −1 (meq·100 g). Averaged overall samples, BS ranged from 15% to 71% of CEC and calcium accounted for 68%, magnesium for 25%, sodium for 5%, and potassium for 1.4% of BS. CEC was positively correlated to the amount of Sphagnum fuscum (Schimp.) Klingrr. in the sample (r = 0.22). BS was positively correlated to the amount of sedge (r = 0.28). Neither CEC nor BS was influenced by degree of decomposition (r = 0.002 and r = 0.08, respectively). Moss peats with high CEC have a greater buffering capacity than those with low CEC, resulting in less pH drift. Moss peats with high BS should have a low neutralization requirement to achieve a target pH. Understanding the species composition in peat-based substrates can alleviate problems of inconsistent initial pH and subsequent pH drift.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".