A search for a correlation between time change in transfer functions and seismic energy release in northern Taiwan
Bibliographic record
Abstract
Abstract The geomagnetic data of the Lunping Geomagnetic Observatory from 1988 to 2000 are utilized for computing daily geomagnetic transfer functions. The method of analysis is based on the power spectrum analysis developed by Everett and Hyndman. Monthly means are statistically obtained from these daily values of transfer functions. In order to compare these time changes with seismic activity (seismicity), the earthquakes occurring within 150 km from Lunping, with a magnitude M L greater than 4.0, are located. The related energy releases by those earthquakes, summed month by month, are correlated to the transfer functions. After removing the seasonal effect, we find that the time changes of magnitude of A u and B u (real parts of the transfer function) for frequencies of 2, 3, 4, and 6 cycles/hour seem to be strongly related to the energy release within the whole study period. Two significant precursors were found from the A and B values, 40 and 20 months before high seismicities, respectively.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".