Polar cap index comparisons with AMIE cross polar cap potential, electric field, and polar cap area
Bibliographic record
Abstract
The polar cap index (PCI) has been shown to be quite useful as an index of the electrodynamic processes within the high‐latitude ionosphere. Here we use between 150 and 180 magnetometers to model the high‐latitude electrodynamics with the assimilative mapping of ionospheric electrodynamics (AMIE) technique for all of 1997–2001. We compare AMIE calculations of the cross polar cap potential (CPCP), polar cap electric field, and polar cap area to the Northern PCI and the existing PCI‐based relationships for these quantities. We find that the existing PCI estimates underestimate all of the AMIE derived quantities. The PCI is best correlated with the CPCP, while it correlates least with the polar cap electric field. In addition, there is a seasonal effect in the relationship between all AMIE quantities and the PCI. It is most pronounced in the electric field. The polar cap area is shown to have a linear fit in the summer and an asymptotic fit in the winter. These differences indicate that there may be a conductance difference in the techniques. We derive new relationships between the Northern PCI and the AMIE derived polar cap area, CPCP, and polar cap electric field which include the seasonal dependence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".