Global Terrestrial Network for Permafrost (GTNet-P): permafrost monitoring contributing to global climate observations
Bibliographic record
Abstract
Active layer and permafrost thermal state have been identified as key cryospheric variables for monitoring through the World Meteorological Organization's Global Climate Observing System. An international network, the Global Terrestrial Network for Permafrost (GTNet-P), has been established under the Global Climate Observing System and is being developed by the International Permafrost Association. The active layer component, the Circumpolar Active Layer Monitoring (CALM) program, is already in place. Global Terrestrial Network for Permafrost organizational efforts are thus focused on the development of the permafrost temperature monitoring program, where Canada contributes actively through the Geological Survey of Canada's membership on the International Permafrost Association organization and implementation committee. Although several regional permafrost borehole temperature networks exist, a globally comprehensive network for ground temperature measurements is required to provide long-term field observations essential for the detection of the climate change signal, for the assessment of its impact on permafrost, and for indications of spatial variability across the permafrost regions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".