Timeseries of Arctic-Boreal Lake Area Derived from CubeSat Imagery, 2017
Bibliographic record
Abstract
This dataset provides near-daily lake area timeseries for 85,358 lakes across four study areas in Northern Canada and Alaska, USA, between May 1 and October 1, 2017. These lake area estimates were produced using digital images from newly developed Planet Labs CubeSats, small satellites with a 4-band (blue, green, red, near-infrared) camera payload. In constellation, CubeSats collected imagery at very high spatial (3-5m) and temporal (near-daily) resolution. From the imagery, each lake's mean, minimum, and maximum areas and seasonal dynamism were derived. The dataset covers four Arctic-Boreal regions: the Yukon Flats Basin (YFB) in eastern interior Alaska, and the Mackenzie River Valley (MRV), Canadian Shield Transect (CST), and Hudson Bay Lowland (HBL) in Canada.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".