The oriented lakes of Tuktoyaktuk Peninsula, Western Arctic Coast, Canada: a GIS‐based analysis
Bibliographic record
Abstract
Abstract The orientation, size and shape of 578 lakes on Tuktoyaktuk Peninsula were obtained from 1 : 250 000 Canadian National Topographic Survey map sheets, using ArcView geographic information system. These lakes are outside the glacial limits in a tundra plain with <15m relief. The lakes range from 20 to 1900 ha, and have mean orientation N07 °E, with standard error 1.6°. The maps show 145 former lake basins, with lakes inset in 130 of these. The mean orientations of the basins and inset lakes are not statistically different from each other or the general population. Several theories have been proposed for the origin of the oriented lakes, and one theory attributes the orientation to cross winds establishing currents that preferentially erode the ends of the lakes. Data from Tuktoyaktuk and Nicholson for 1970–95 indicate a consistent wind regime within the region, with prevailing winds from the east and west. Using data from Nicholson, a geometric model generates resultant lake orientations of N if all winds are considered, and N08 °E if winds above 30km h−1 are used. The coincidence of the modelled orientation and lake statistics supports the efficacy of cross wind‐induced effects in orienting the lakes. The similar orientation of existing lakes and former basins suggests that these processes have been effective for at least several centuries. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".