Active Layer Data from the Yukon River Basin in Alaska and Canada
Bibliographic record
Abstract
The active layer data available here has been collected as part of a collaborative monitoring project between the US Geological Survey, Yukon River Inter-Tribal Watershed Council, and Yukon River Basin communities known as the Active Layer Network (ALN). The active layer is the layer of soil above the permanently frozen ground (permafrost) that thaws during the summer months and freezes again in the autumn. By measuring the depth of the active layer in the late summer at the time of maximum thaw, we are able to better understand the effects of a warming climate on permafrost. ALN monitoring sites were installed across the Yukon River Basin, in Alaska and Canada, in 2009 and 2010. Each monitoring site consists of a 45 meter by 45 meter grid and sensors. Active layer depth measurements are taken every 5 meters across the grid resulting in 100 measurements made each year. Sensors installed at each location include soil moisture, soil temperature, and air temperature sensors. Sensor data is collected throughout the year and downloaded annually. Active layer depth measurements and sensor data are presented here.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".