Organic carbon, organic matter and bulk density relationships in boreal forest soils
Bibliographic record
Abstract
Relationships between soil organic carbon (SOC), organic matter (SOM), and bulk density (BD) were established in acidic loamy to sandy loam fine fractions of forest soils in Quebec (Canada). The interest of such relationships rests with the possibility of using simple and rapid techniques to estimate SOC and BD. It is also a crucial step in establishing the correspondence among several databases when SOC data are obtained using different measurement techniques. In this study, SOC was measuredby dry combustion (SOCNDC) and wet digestion (SOCWD) methods, and organic matter by loss-on-ignition (LOI). Our results suggest that, in these soils: (1) LOI can be used for estimating SOC (r2 = 0.95, RMSEP = 16%) and SOCDC/SOM significantly decreased with increasing depth from 0.49 to 0.27; (2) SOCDC and SOCWD were highly correlated. Even if SOCWD provided near complete recovery of SOCDC, dry combustion remains the preferred method for SOC analysis since recovery decreased with increasing depth from 100 to 83%. (3) BD was also strongly related to SOM(r2 = 0.81). We recommend using the organic density approach to estimate BD from SOM because it allows BD to be predicted without significant bias and with a degree of accuracy of 14%. Key words: Forest soils, soil organic carbon, soil organic matter, soil bulk density
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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 | 0.001 | 0.000 |
| 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".