Surface Water and Ocean Topography (SWOT) mission
Bibliographic record
Abstract
The Surface Water Ocean Topography (SWOT) mission was recommended in 2007 by the National Research Council’s Decadal Survey, “Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond”, for implementation by NASA. The SWOT mission is a partnership between two communities, the physical oceanography and the hydrology, to share high vertical accuracy and high spatial resolution topography data produced by the science payload, principally a Ka-band radar Interferometer (KaRIn). The SWOT payload also includes a precision orbit determination system consisting of GPS and DORIS receivers, a Laser Retro-reflector Assembly (LRA), a Jason-class nadir radar altimeter, and a JASON-class radiometer for tropospheric path delay corrections. The SWOT mission will provide large-scale data sets of ocean sea-surface height resolving scales of 15km and larger, allowing the characterization of ocean mesoscale and submesoscale circulation. The SWOT mission will also provide measurements of water storage changes in terrestrial surface water bodies and estimates of discharge in large (wider than 100m) rivers globally. The SWOT measurements will provide a key complement to other NASA spaceborne global measurements of the water cycle measurements by directly measuring the surface water (lakes, reservoirs, rivers, and wetlands) component of the water cycle. The SWOT mission is an international partnership between NASA and the Centre National d’Etudes Spatiales (CNES). The Canadian Space Agency (CSA) is also expected to contribute to the mission. SWOT is currently nearing entry to Formulation (Phase A). Its launch is targeted for October 2020.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".