Pacific Walrus Coastal Haulout Occurrences Interpreted from Satellite Imagery
Bibliographic record
Abstract
This dataset is derived from images from a variety of Earth observing satellite imagery sources collected at known walrus coastal haulouts in Alaska and Chukotka, Russia. Earth observing imagery sources used in this data release include (but are not limited to) optical imagery collections by: (1) the European Space Agency's Sentinel-2 mission, (2) the Plant Labs Planet Scope constellation, and (3) Maxar satellites, as well as synthetic aperture radar imagery collected by: (1) European Space Agency's Sentinel-1 mission, (2) the DLR (German Aerospace Agency) TerraSAR-X satellite, (3) the Umbra Space satellite constellation, (4) the Canadian Radarsat-2 satellite, (5) the Capella Space satellite constellation and (6) the Finnish Iceye constellation. This data package provides: A) geospatial polygon outlines of walrus herds apparent to trained interpreters in satellite images; B) a table listing the satellite images examined that had clear views of the walrus coastal haulout study sites and the area of all walrus herds (if any were present) summarized from the geospatial polygon outlines of walrus herds apparent to trained interpreters, and C) maps (not available for all haulouts in all years) showing interpreted herd outlines superimposed on the satellite images.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.014 |
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".