Bibliographic record
Abstract
We would like to propose ceasing the derivation and distribution of the AE (Auroral electrojet) index because AE has no physically interpretable meaning and is therefore of no scientific value. Note that the term “ AE indices” is different from the term “ AE index;” the former includes the AU and AL indices, whereas the latter is just the AE index itself. (See below for the definition of AU and AL .) Since the introduction of the AE indices by Davis and Sugiura [1966], scientists have relied on the indices to monitor the level of geomagnetic disturbance resulting from the auroral electrojets and hence, by proxy, to specify the state of the magnetosphere and the ionosphere. The AE index was defined by the separation between the upper and lower envelopes of the superposed H component plots from auroral‐zone magnetic observatories. The upper and lower envelopes were defined as the AU and AL indices, respectively Thus, there is the relationship given by AE = AU ‐ AL .
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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".