The cover art by Emma Spanswick is a composite of the photographs by Jouni Jussila (auroras)
Bibliographic record
Abstract
Preface In March 2006, roughly 140 substorm researchers from around the world descended on Banff Canada for the Eighth International Conference on Substorms (ICS VIII). The meeting was held at The Banff Centre which provided a beautiful venue for the event. Two satellite meetings were held on the preceding weekend. These were a storm-substorm relationship workshop, and the Second International Riometer Workshop. Both drew around 20 attendees, many of whom stayed for ICS VIII. In the time leading up to ICS VIII, it was clear that while we are in an exciting period of substorm research, there is frustration in the space physics community related to this topic. On the one hand, recent observational, theoretical, and simulation work has uncovered fascinating new facets of the substorm problem. For observational examples, we now have direct and unambiguous observations of mid-tail reconnection from Geotail and Cluster, and we are developing a clear picture of the global evolution of the magnetosphere during the substorm, its role in the storm, and interesting new global substorm related phenomena such as sawtooth events. On the theo-retical and simulation side, great progress has been made in the use of simulations ranging from
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.285 | 0.121 |
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".