Structure-from-Motion Snow Depth Products and In Situ Observations for Late-Winter Tundra Mapping Project, Trail Valley Creek Research Station, Spring 2018
Bibliographic record
Abstract
Presented here is the final dataset accompanying the publication, ,"Accuracy Assessment of Late Winter Snow Depth Mapping for Tundra Environments Using Structure-From-Motion Photogrammetry" submitted to Arctic Science, in Spring 2020. Included within are seven Structure-from-Motion (SfM) photogrammetry snow depth maps produced using a fixed-wing Unmanned Aerial System (UAS) and the methods described within the corresponding manuscript. In situ observations of snow depth collected using a Magnaprobe snow depth probe and snow-surface elevations are also included in separate CSV files and represent the final dataset used for ground validation during the 2018 March and April field campaigns at Trail Valley Creek, Northwest Territories, Canada. A readme file is included containing important information on data collection, processing and QA/QC including UAS flights protocol, RTK GNSS benchmark coordinates and elevation datum, and processing steps for each snow depth map presented.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".