Digital Soil Mapping at multiple scales in British Columbia, Canada.
Bibliographic record
Abstract
Digital soil mapping (DSM) is being implemented to improve soil information for the Canadian province of British Columbia. This paper reports on progress made in two related initiatives. The first involves spatial disaggregation of detailed/semi-detailed (1:20,000- 1:125,000), harmonized, legacy soil survey information using a 25 m DEM and several automated landform classification systems including a fuzzy land element approach, unsupervised nested-means algorithm and a simple topographic position index. Selective landform facet classes and additional co-variates including solar radiation and ecological subzones are used as input variables to ArcSIE software to predict the occurrence of individual soil series and their attributes over a semi-arid high relief watershed of approximately 8,200 km 2 in southern British Columbia. A second initiative evaluates techniques utilizing map components from the 1:1,000,000 Soil Landscapes of Canada map series to predict soil attributes on a 100 m DEM. The province-wide prediction efforts address some of the key data and methodological challenges facing the GlobalSoilMap.net project for the mountainous western Canadian landscape where soil maps are readily available for many areas but point (pedon) data are limited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".