A hydrometeorological dataset from the taiga-tundra ecotone in the western Canadian Arctic: Trail Valley Creek, Northwest Territories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>Across the Arctic, we are observing climate system feedback with permafrost thaw, rising air temperatures, changes in surface and subsurface hydrology, vegetation, wildlife and northern communities. There is a need for high quality and long duration records, with datasets targeting characteristics of snow, hydrology, vegetation, sub-surface thermal properties of the permafrost, and fluxes of water and energy. The Laurier Trail Valley Creek (TVC) Arctic Research Station, approximately 50 km north of Inuvik (NT, Canada) in the low Arctic tundra, was established in 1991. With scattered patches of tall shrubs and spruce forests, TVC is underlain with ice-rich continuous permafrost approximately 150 – 350 meters in depth, with ice-wedges, tabular ice, segregated ice, thermokarst lakes and drained lakes. The research station hosts teams of interdisciplinary, multi-institutional research groups from across Canada and other countries. A core aspect of hydrological research at TVC is the integration of distributed snow mapping, eddy covariance measurements of energy and water between the Arctic tundra landscape and atmosphere, lake levels and streamflow, extensive remote sensing and high-resolution spatially distributing modelling. </p><p> The multi-decadal TVC dataset described here includes: </p> <ul> <li>Weather station data (1991-2025)</li> <li>End of winter distributed snow observations (1991-2025)</li> <li>Gap-filled meteorological data (1991-2023)</li> <li>Daily TVC discharge from the Environment and Climate Change Canada hydrometric station (10ND002) (1977-2025)</li> <li>TVC watershed boundaries</li> </ul>
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.013 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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 it