Comparison of Multi-element Extraction Methods to Determine Available Phosphate and Exchangeable Cations of Korean Soils
Bibliographic record
Abstract
Soil testing is one of the best management practices for sustainable agriculture. Recently, as increasing soil testing needs, simplification of soil analytical procedure has been required. To determine recommendable multi-element extractant, the soil testing results of available phosphate and exchangeable cations between the conventional methods (Lancaster and 1M ) and multi-element extraction methods such as Mehlich III, Modified Morgan and Kelowna methods were compared. There were highly significant correlation between the conventional methods and multi-element extraction methods (Mehlich III, Modified Morgan and Kelowna) for available phosphate and exchangeable K, Ca, Mg and Na. The coefficients of determination () between available phosphate extracted by Lancaster method and multielement extraction methods were in the order of Mehlich III () > Kelowna () > Modified(Mod.). Morgan (). For exchangeable cations, there were highly significant correlations between 1M method and Mehlich III, Mod. Morgan and Kelowna. However, exchangeable K, Ca and Mg by Mehlich III method were more highly correlated with conventional method than other methods. Therefore, Mehlich III extraction method could be recommended as a single extractant for simultaneous measurement using ICP in the analysis of avaliable phosphate and exchangeable cations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".