Equivalent latitude for prediction of soil development in a complex mapunit
Bibliographic record
Abstract
Whitson, I. R. 2015. Equivalent latitude for prediction of soil development in a complex mapunit. Can. J. Soil Sci. 95: 125-137. Soil pattern in the Hillwash complex mapunit from Saskatchewan is too variable to be resolved spatially with conventional mapping approaches. The equivalent latitude metric allows identification of an index based on gradient and aspect that ranks sites based on differences in direct radiant energy inputs. Effects on soil development with reference to surface horizon color and soil classification were investigated at three study areas in southern Saskatchewan. At the first, sites with equivalent latitude greater than local latitude (north group) had a higher frequency of darker soil colors than sites where equivalent latitude was less than local latitude (south group). Black Chernozemic profiles made up nine of 13 profiles from the north group compared with none in the south group or in local controls. Similar color and classification trends in a north sample group were found at a second study area. Results from a third study area more than 200 km away and in a drier ecoregion found similar differences albeit a different set of subgroups between north and south group soils at that location. The equivalent latitude metric could be used in a GIS context to better resolve soil characteristics within this complex mapunit, but only after additional work to include a climate parameter such as potential transpiration into the model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".