Slope per SASAP region and Hydrolic Unit (HUC8) boundary for Alaskan watersheds
Bibliographic record
Abstract
This dataset was created to assess regions and watersheds of Alaska for mean slope, minimum slope, maximum slope, median slope, standard deviation of slope, range of slope and coefficient of variation of slope in each SASAP region and each HUC8 watershed of Alaska. Three DEM's were mosaicked to make an Alaska-wide tiff. These include separate files for Alaska, the Yukon, and British Columbia. They were combined with the "sasap_regions.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create the shapefile, "regions_slope_shp.zip" and with the "sasap_watersheds_gapfix.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create the shapefile "watersheds_slope_shp.zip". CSV versions of the resulting shapefiles are also archived. The included python script, which was used to merge the data, outlines the process in more detail.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.023 |
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".