Scientific aspects of the Earth clouds, Aerosols, and Radiation Explorer (EarthCARE) mission
Bibliographic record
Abstract
In recent years remote sensing of cloud, aerosol, precipitation, and radiation has benefited greatly from simultaneous application of multiple sensors. For example, combinations of passive radiometers with active sensors such as lidar or radar have proved to be invaluable for their ability to retrieve profiles of cloud macrophysical and microphysical properties. This is amply illustrated by results from both surface sites, such as the US-DoE's ARM installations, and sensors aboard A-train satellites; namely CloudSat, CALIPSO, and Terra. The Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission, a combined ESA/JAXA endeavor set for launch in 2015, has been designed to host active and passive sensors on a single low-Earth orbit satellite and thus retrieve, through synergistic use of data, the most comprehensive global survey of the vertical structure cloud, aerosol precipitation, and radiation. The mission consists of a cloud-profiling radar, a high-spectral resolution cloud/aerosol lidar, a passive imager, and a threeview broadband radiometer (BBR) covering both longwave and shortwave bands. The mission will deliver cloud, aerosol and radiation products focusing on horizontal scales ranging from 1 km to 10 km at a vertical grid-spacing of 0.1 km.
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 | 0.000 | 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) | 0.002 | 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".