Cryosolic soils of Canada: Genesis, distribution, and classification
Bibliographic record
Abstract
Tarnocai, C. and Bockheim, J. G. 2011. Cryosolic soils of Canada: Genesis, distribution, and classification. Can. J. Soil. Sci. 91: 749-762. Cryosols are permafrost-affected soils whose genesis is dominated by cryogenic processes, resulting in unique macromorphologies, micromorphologies, thermal characteristics, and physical and chemical properties. In addition, these soils are carbon sinks, storing high amounts of organic carbon collected for thousands of years. In the Canadian soil classification, the Cryosolic Order includes mineral and organic soils that have both cryogenic properties and permafrost within 1 or 2 m of the soil surface. This soil order is divided into Turbic, Static and Organic great groups on the basis of the soil materials (mineral or organic), cryogenic properties and depth to permafrost. The great groups are subdivided into subgroups on the basis of soil development and the resulting diagnostic soil horizons. Cryosols are commonly associated with the presence of ground ice in the subsoil. This causes serious problems when areas containing these soils are used for agriculture and construction projects (such as roads, town sites and airstrips). Therefore, where Cryosols have high ice content, it is especially important either to avoid these activities or to use farming and construction methods that maintain the negative thermal balance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".