Special issue “Recent Advances in MST and EISCAT/Ionospheric Studies – Special Issue of the Joint MST15 and EISCAT18 Meetings, May 2017”
Bibliographic record
Abstract
The Fifteenth Workshop on Technical and Scientific Aspects of MST Radar (MST15) and the Eighteenth EISCAT Symposium (EISCAT18) were jointly held in Tokyo, Japan, at the National Institute of Polar Research (NIPR) during May 26–31, 2017. The MST workshops have a long history of being the primary international meetings on the applications and development of mesosphere–stratosphere–troposphere (MST) radars. The MST workshop has been historically focusing on the atmospheric dynamics but is now including topics related to ionospheric applications of radars. The EISCAT Symposium, on the other hand, is the biennial conference for EISCAT-related radar research and science which is hosted by member institutions of the EISCAT Scientific Association.<p><p>\n\nThis joint MST15/EISCAT18 meeting was a timely opportunity for close and extensive interactions of the middle-atmosphere and ionospheric radar scientists in our era of rapid technological changes and computational advances. The joint meeting was successfully attended by 182 participants from 19 countries/areas and hosted 233 presentations. These numbers were the maximum level ever for either conferences.<p><p>\n\nThis special issue gathered 15 papers from this joint meeting, consisting of ten full papers, three frontier/express letters and two technical reports. The flexible publication style of Earth, Planets and Space benefitted us to cover easily both scientific and technical aspects of the research field. In the following, we categorize the articles into several groups and review them briefly.
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".