Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins
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. Past characterizations of the land–ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems). Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation) and 149 sub-units (COSCATs). Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric profiles. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air–water interface combining global and regional average emission rates derived from local studies.
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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 | 0.000 | 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