A deployable spaceborne lidar telescope: concept and technology advances
Bibliographic record
Abstract
Over the past five years the feasibility of spaceborne differential absorption lidar (DIAL) systems for the purposes of trace gas monitoring in the atmosphere has been studied [1,2,3]. The feasibility of such instruments is supported by the results of studies such as ORACLE (Ozone Research with Advanced Cooperative Lidar Experiment: a joint study of NASA/LaRC and the Canadian Space Agency) and WALES (Water vApor Lidar Experiment in Space: a study by the European Space Agency). One crucial aspect determining spaceborne DIAL performance is the collecting telescope's aperture size. In this respect, the interests of the atmospheric remote sensing and the astronomy communities overlap, in that spaceborne telescope aperture size is a key performance driver for both applications. While the stringent optical performance requirements characteristic of astronomical instruments -and the success seen in reaching some of these goals for the Next Generation Space Telescope (NGST)- are encouraging for the realization of more modest spaceborne lidar telescope optical performance requirements, spaceborne DIAL telescope development nevertheless provides its own challenges.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".