Dry Combustion Carbon, Walkley–Black Carbon, and Loss on Ignition for Aggregate Size Fractions on a Toposequence
Bibliographic record
Abstract
Accurate and simple methods for determining soil organic carbon that do not involve the use of chemicals that damage the environment are required. Dry combustion carbon, Walkley–Black carbon, and loss on ignition (LOI) were determined on whole soils (<2000 µm) and aggregate size fractions (250–2000 µm, 53–250 µm, <53 µm) collected from a toposequence, part cropped and part under forest regrowth. For each group, the Walkley–Black correction factor averaged 1.2, which was less than the usually assumed factor of 1.3. Both temperature and sample weight had significant effects on LOI, but the former had a greater effect. There were strong correlations between LOI and dry combustion carbon for all aggregate size fractions. Highest coefficient of determination (R2=0.89–0.93) were obtained for 1‐g soil samples ignited at 375°C for 2 h; under these conditions, slopes and intercepts of the regressions of organic carbon on LOI were not significantly different among aggregate fractions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".