Gray Luvisols are polygenetic
Bibliographic record
Abstract
With respect to the pedosphere, human activities in the last 100 years have been the major driver of soil change. Despite human activities being one of the main soil forming factors recognized by soil scientists (in addition to climate, organisms, parent material, relief, groundwater, and time), the Canadian System of Soil Classification (CSSC) emphasizes soil as a natural body. We argue human agricultural activities are direct and indirect drivers of significant changes to the carbon balance and cycling in A horizons of Gray Luvisolic soils in western Canada, resulting in changes to A horizon carbon stocks, structure, and micromorphology. Evidence from scientific literature, in-field soil profile observations, and the National Pedon Database are presented in support of our argument. We propose a polygenetic, two-stage model of Gray Luvisol soil formation. The first stage is dominated by the climate forcing of the Holocene, resulting in a relatively stable boreal forest ecosystem including perturbations from natural and human-induced wildfire and other disturbances. The second stage is dominated by direct, human-driven disturbances such as cultivation, release of exotic fauna (earthworms), and indirect human-driven disturbances associated with anthropogenic climate change. Further, we propose modest amendments to the CSSC to reflect a polygenetic model of soil genesis in Gray Luvisolic soils that preserve the balance between observation and interpretation inherent in the system.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".