A proposed framework for assigning soil drainage classes to non-redoximorphic soils in the Canadian System of Soil Classification
Bibliographic record
Abstract
Drainage refers to the frequency and duration of periods of saturation, and how quickly excess water is removed from the soil profile. It is one of the central concepts used to differentiate soil series within the Canadian System of Soil Classification (CSSC). Currently, seven drainage classes are recognized in the CSSC: very rapid, rapid, well, moderately well, imperfect, poor, and very poor. In redoximorphic soils (imperfect, poor, and very poor drainage classes), drainage is typically differentiated based on morphological features (i.e., the presence of gleying and mottles). Non-redoximorphic soils (very rapid, rapid, and well-drained classes) do not display such morphological features but are differentiated based on available water holding capacity (AWHC) as inferred from soil texture and particle size. Moderately well-drained soils are intermediate, in some cases defined by the presence of redoximorphic characteristics, but in other cases inferred based on texture. In effect, drainage in materials without redoximorphic features is estimated based on AWHC as related to texture class, which should include sand subfractions. Values for AWHC were calculated using a published pedotransfer function for combinations of sand, silt, and clay-sized particles, including various combinations of very fine to very coarse sand separates as input. Calculated values were compared with currently assigned drainage classes and several inconsistencies were identified. Revisions are proposed to textural assessment of soil drainage for non-redoximorphic 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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".