White Glacier 2014, Axel Heiberg Island, Nunavut: mapped using Structure from Motion methods
Bibliographic record
Abstract
We use Structure from Motion software to generate a new digital elevation model (DEM) of White Glacier, Axel Heiberg Island, Nunavut, using >400 oblique aerial photographs collected in July 2014. Spatially and radiometrically high-resolution imagery, optimized camera settings, low angle lighting conditions, and photo post-processing methods together supported the detection of small but distinct features on the surface of the snowpack and enabled feature matching during the image correlation process. The resulting DEM and orthoimage facilitated the production of a new 1:10,000 topographic map with 5 m vertical accuracy in the style of earlier cartographic works of White Glacier dating back to 1960. The new map of White Glacier will support calculation of the glacier's geodetic mass balance (mass change determined from ice volume change over the past 54 years) and provides an updated glacier hypsometry (area-elevation distribution) that will improve the accuracy of future mass balance calculations.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".