A cross-discipline approach to examine the physical links between Weather in Space and the Lower Atmosphere
Bibliographic record
Abstract
Earth’s atmosphere provides the background for the “sea of plasmas” surrounding Earth via its Ionosphere and the upper and middle Atmosphere, providing an interface layer through which a broad diversity of solar-terrestrial energy transfer processes takes place. Developing an integrative understanding of global geospace energy transfer processes affecting this layer is a major scientific challenge with important societal implications. The disciplines covering this interaction have a large, diverse and active international community, with significant expertise and heritage in the European Space Agency and Europe. Several ESA directorates have activities directly connected with this topic, and an ESA Heliophysics Working group has been appointed by several ESA Directors, under the direction of the ESA Director General, to work on optimizing synergies and to act as a focus for discussion, inside ESA, of the scientific interests of the Heliophysics community.Very recently, a Forum at the International Space Science Institute was set up, involving some of the above WG, to look towards developing a deeper understanding of the solar-terrestrial interactions between the Ionosphere and the upper- and middle atmosphere, thus possibly enabling the detection of signatures by natural and anthropogenic hazards.This presentation will provide a brief introduction to ongoing internal ESA cross discipline approaches, and then note some of the outcomes of this recent ISSI forum to set out a pathway to address this intriguing topic.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".