High-resolution global topographic index values
Bibliographic record
Abstract
The topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution. PLEASE NOTE: This dataset is a correction to a previous version which was found to contain errors ( https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da ). In the previous version all pixels north of 4.57 degrees south were shifted consistently 9.3 km to the west. This version is correctly aligned at all points.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.038 |
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".