Bibliographic record
Abstract
Abstract The solution of reduction to the pole (RTP) of magnetic data in the wavenumber domain faces a long standing difficulty of instability when the observed data are acquired at low magnetic latitudes or at the equator. We develop a solution to this problem that allows stable reconstruction of the RTP field with a high fidelity even at the magnetic equator. The solution is obtained by inverting the Fourier transform of the observed magnetic data in the wavenumber domain with explicit regularization. The degree of regularization is chosen according to the estimated error level in the data. The Fourier transform of the RTP field is constructed as a model that is maximally smooth and, at the same time, has a power-spectral decay common to all fields produced by the same source. The applied regularization alleviates the singularity associated with the wavenumber-domain RTP operator, and the imposed power spectral decay ensures that the constructed RTP field has the correct spectral content. As a result, the algorithm can perform the reduction to the pole stably at any magnetic latitude, and the constructed RTP field yields a good representation of the true field at the pole even when the reduction is carried out at the equator.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".