Global hydro-environmental lake characteristics at high spatial resolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Here we introduce the LakeATLAS dataset, which provides a broad range of hydro-environmental characteristics for more than 1.4 million lakes and reservoirs globally with an area of at least 10 ha. LakeATLAS forms part of the larger HydroATLAS data repository and expands the existing datasets of sub-basin and river reach descriptors by adding equivalent information for lakes and reservoirs in a compatible structure. Matching its HydroATLAS counterparts, version 1.0 of LakeATLAS contains data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. LakeATLAS derives these attributes by processing and reformatting original data from well-established global digital maps at 15 arc-second (~500 m) grid cell resolution and assigns the information spatially to each lake by aggregating it within the lake, in a 3-km vicinity buffer around the lake, and/or within the entire upstream drainage area of the lake. The standardized format of LakeATLAS ensures versatile applicability in hydro-ecological assessments from regional to global scales.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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 it