Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Understanding the geomagnetic hazard to power systems requires the ability to model the geomagnetically induced currents (GIC) produced in a power network. This paper presents the developments in GIC modeling starting with an examination of fundamental questions about where the driving force for GIC is located. Then we outline the two main network modeling approaches that are mathematically equivalent and show an example for a simple circuit. Accurate modeling of the GIC produced during real space weather events requires including the appropriate system characteristics, magnetic source fields, and Earth conductivity structure. It is shown how multiple voltage levels can be included in GIC modeling and how the network configuration affects the GIC values. Magnetic source fields can be included by using “plane wave” or line current models or by using geomagnetic observatory data with an appropriate interpolation scheme. Earth conductivity structure can be represented by 1‐D, 2‐D, or 3‐D models that are used to calculate the transfer function between electric and magnetic fields at the Earth's surface. For 2‐D and 3‐D structures this will involve a tensor impedance function and electric fields that are not necessarily orthogonal to the magnetic field variations. It is now technically possible to include all these features in the modeling of GIC, and various software implementations are being developed to make these features more accessible for use in risk studies.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.013 | 0.003 |
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 it