Effects of station relocation in the <i>aa</i> index
Bibliographic record
Abstract
Earlier studies have shown that the long‐term measure of geomagnetic activity, the aa index, is inhomogeneous and depicts an excessively large (about 12 nT) centennial increase. This has preliminarily been suggested to be due to possible station intercalibration problems in 1957 when the northern aa station was changed from Abinger to Hartland. In the present paper we show that the 3‐hourly aa index time series is not uniform but includes systematic jump‐like changes in the distribution of the various aa values with each change of stations in 1920, 1926, 1957, and 1980. We estimate how large a change to the aa index was caused by each particular aa value. We find that the changes to the aa index due to different ranges of activity are smooth and fairly similar for all jumps. In 1957 the largest aa values had, at the expense of more moderate aa values, a relatively larger contribution to the jump than in other station changes because the relative station coefficient was somewhat larger in 1957, leading to larger spreading and a higher average level of aa values. However, while this difference could cause a slight overestimate of the aa values, we find that the total changes in the aa index over jumps are in agreement, in both sign and magnitude, with the solar cycle variation. So it is unlikely that the excessive increase of the aa index would be due to erroneously estimated station coefficients.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".