A comprehensive framework for integrating lake hypsography and function on a global scale
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
As climate change and nutrient pollution intensify, understanding how millions of lakes will respond to such forcings as a global or regional collective has become urgent and yet capturing their role in Earth's system remain neither conceptually unified nor empirically constrained. Here we introduce a framework that aggregates individual lake hypsography and functional attributes into composite lakes globally, across climate zones or 1-degree Earth system grid cells. We find that globally, lake shape mirrors land rather than ocean, with shallow areas dominating. This structure reveals systematic differences between glaciated and non-glaciated regions and between colder and warmer climate zones. At the 1-degree Earth system grid cells, composite lakes group into five distinct clusters. Globally, an estimated 43% of lake volume and sediment surface area lie within the mixed layer. A composite mixed layer volume-to-sediment-surface-area ratio reveals dominant water column influence and biogeochemical sensitivities, with strong contrasts across climates and glacial histories. The proposed framework advances quantifying and understanding the collective role of lakes across spatial scales in Earth's system.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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