Models for potassium release kinetics of four Humic Gleysols high in clay by electro-ultrafiltration
Bibliographic record
Abstract
The rate of K release from the soil solid phase to its solution, especially from its rapidly and slowly exchangeable forms, can affect plant K uptake. The electro-ultrafiltration (EUF) technique was used to kinetically characterize the K release from four soils (Humic Gleysols) from Abitibi-Temiscaming, Quebec, Canada. Potassium was desorbed from soils that received over 166 kg K ha-1 yr-1 from 1994 to 1996. The desorption was carried out for 58 min (4, 4, and every 5 min thereafter for a total of 12 desorptions) at 400 V and 80°C. The amount of K desorbed was between 199 and 342 mg kg-1. Cumulative K desorption was described by the following six equations: power function, simplified Elovich, extended Elovich, parabolic diffusion, zero-order, and first-order. An incremental first-order equation was also tested. The studied soils have large K supplying capacities as suggested by forage K-uptake and total soil K desorption by EUF. In general, all tested equations adequately described the K release by EUF from the four soils. The incremental first-order equation, used for the first time, described well the soil K release data. The k rate constant from this model was significantly related to forage K uptake (R2 = 0.58). Results from this study indicate that the investigated soils have large K reserves and that the incremental first-order equation and most of the cumulative ones are suitable for describing the kinetics of the large K release from these fine-textured Gleysols. Key Words: Potassium, desorption, cumulative model, incremental model
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".