Circumpolar digital elevation models > 55° N with links to geotiff images
Bibliographic record
Abstract
In order to generate a global DEM elevation information from the\nfollowing datasets were considered:\n* SRTM-3 DEM (Shuttle Radar Topography Mission)\n* RTM (Russian Topographic Maps)\n* CDED (Canada Digital Elevation Data)\n* U.S. Geological Survey DEM (for Alaska).\nAll datasets have been downloaded and checked for coverage and quality before further processing. For each dataset, description of image specifications, processing applied and quality control is provided in the product guide. The database of elevation provided to the DUE Permafrost project consists of tiles with following specification\n* Latitude coverage: > 55 deg N\n* Longitude coverage: full\n* Elevation: as in original datasets\n* Projection: equiangular, i.e. latitude/longitude\n* Ellipsoid/datum: WGS-84\n* Elevation data on the integer degree lines (all four sides) overlap with the corresponding profiles on the surrounding eight blocks.\n* Tile coverage: 1 X 1 deg, posting: 3 arcsec = 0.0008333333 deg (i.e., approximately 90 m at Equator)\nSee hdl:10013/epic.39123.d024 for an overview figure. The product guide: hdl:10013/epic.39123.d013.\nThis dataset is part of the ESA Data User Element (DUE) Permafrost Full Product Set (doi:10.1594/PANGAEA.780111).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.135 | 0.156 |
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".