Lake- and channel-bottom temperatures in the Mackenzie Delta, Northwest Territories<sup>1</sup>This article is one of a series of papers published in this CJES Special Issue on the theme of <i>Fundamental and applied research on permafrost in Canada</i>.<sup>2</sup>Polar Continental Shelf Project Contribution 03511.
Bibliographic record
Abstract
Temperature loggers were placed in 17 lakes and 13 channels throughout the Mackenzie Delta to determine the annual mean bottom temperature ([Formula: see text]) and its spatial and temporal variation for June 2009 – June 2010. The lakes were classified as perched or connected, depending on the duration of their connection to the channel hydrologic system. Average [Formula: see text] values for nine perched lakes, five channels, and eight connected lakes distributed throughout the Mackenzie Delta were 5.5, 4.6, and 3.4 °C, respectively. The range of [Formula: see text] among all instrumented water bodies in the Delta was 4.0 °C. Over the year, bottom temperatures ranged from >20 °C in midsummer to –5 °C in midwinter, with relative stability between freeze-up in mid-October and breakup at the beginning of June. Channel, perched, and connected lake [Formula: see text], and mean annual near-surface ground temperatures of –4 °C in alluvial sedge wetlands and –2.25 °C in forest, were used to estimate that about 60% of Delta lakes and nearly the entire channel network maintain through-taliks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".