Soil Temperature (5 cm) Records from Agricultural Weather Stations in Canada Aligned with Sentinel-1 Overpasses (October to June, 2016-2023)
Bibliographic record
Abstract
This dataset contains soil temperature measurements at a depth of 5 cm from agricultural weather stations across four Canadian provinces: Alberta, Manitoba, Saskatchewan, and Québec. The data spans from October 2016 to June 2023 and is aligned with Sentinel-1 SAR overpasses. The dataset provides comprehensive spatial coverage, with records from 174 weather stations situated in diverse agricultural and climatic conditions. It is primarily intended for research in freeze-thaw detection. The dataset includes the latitude and longitude of each weather station, crop type data from Agriculture and Agri-food Canada annual crop inventory, and soil type data from the Detailed Soil Survey (DSS) of the National Soil Database (NSDB), supplemented by digital soil mapping from the World Soil Information Service (WoSIS). The soil temperature data is available based on the temporal resolution of Sentinel-1 overpasses at each given station. For more information, refer to the ReadMe file.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.016 |
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".