Observing earth’s sodium and atomic oxygen dayglow emissions <sup>1</sup>This article is part of a Special Issue that honours the work of Dr. Donald M. Hunten FRSC who passed away in December 2010 after a very illustrious career.
Bibliographic record
Abstract
The observation of sodium emission in the twilight upper atmosphere was the leading edge of the study of metals in the upper atmosphere, and its quantitative measurement and analysis were pioneered by Donald M. Hunten. He extended these early observations into the daytime, the sodium dayglow, including rocket observations of this phenomenon. More than fifty years later the amount of information on this subject has grown enormously through LIDAR observations, laboratory measurements, and extensive modeling. The author’s participation in those early measurements inspired him to undertake observations of the atomic oxygen dayglow, first from the ground, and then from orbit with the WINDII instrument on NASA’s Upper Atmosphere Research Satellite. The parallels between the Na and O dayglows are described and reviewed, including in particular the methods of observation. Very recent results on the atomic oxygen O(1S) dayglow are presented, showing the influence of the DE3 nonmigrating tide reaching from the troposphere to 250 km altitude in the thermosphere.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".