The soil skeleton, a forgotten pool of carbon and nitrogen in soil
Bibliographic record
Abstract
Summary To evaluate the contribution of rock fragments to the soil’s total carbon content, the soil of 26 sites, ranging from the Canadian Arctic to the Jordan desert, was analysed for the content of organic C and total N in both fine earth and skeleton fractions. The soils, uncultivated and cultivated, are derived from 11 parent materials: sandstone, mica‐schist, granite, gneiss, basaltic pyroclastites, trachyte, dolomite, beach deposits, clay schist, marl and serpentinite. For each soil horizon the contents of fine earth and skeleton were determined by volume. Both fractions were analysed for bulk density, total and organic C and total N. Our results indicate that rock fragments contain amounts of C and N that depend on the nature of the parent material and on its resistance to the weathering processes. The C and N of both fine earth and skeleton were used to calculate the contents of these elements for three depths. At each depth, the skeleton contributes C and N to the soil depending on its abundance. We conclude that the contribution of the rock fragments to the soil C and N cannot be predicted from the soil taxa, but can from the parent material. Calculations that exclude C and N of the skeleton could lead to errors in the estimates of these two elements in soils.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".