Borehole and near-surface ground temperatures in northeastern Canada
Bibliographic record
Abstract
Permafrost is the foundation upon which northern ecosystems and communities rest and upon which new industrial infrastructures are built. Determining the thermal state and dynamics of permafrost soils is therefore of broad interest to many disciplines and users. The purpose of this project is to evaluate the thermo-dynamical processes in various geological, climatic, municipal and industrial settings that lead to permafrost thaw from climate forcing and terrain disturbance. The data are from 11 sets of locations in Nunavik and Nunavut, northeastern Canada. The measurement sites are part of the SILA network of the Center for Northern Studies (CEN - Centre d’études nordiques); climate data are also available in other issues of Nordicana D. The available datasets cover the period from 1988-2023. For each set of locations, the number of boreholes and their depth ranges are as follows: Akulivik: 2 sites, Aupaluk: 2 sites, Kangiqsualujjuaq: 2 sites, Puvirnituq: 2 sites, Quaqtaq: 1 site, Tasiujaq: 2 sites, Umijuaq: 1 site, Iqaluit: 6 sites, Pangnirtung: 8 sites, Île Bylot 3 sites. In Salluit, the temperature data were recorded by Hobo temperature loggers near the ground surface at 21 different sites. Table 1 shows the depth range for the sites. The ground temperature data (oC) are available as: (1) recorded data, which are the averages of 60 measurements at minute intervals over each previous hour; (2) daily averages; (3) monthly averages; and (4) yearly averages.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".