A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation
Bibliographic record
Abstract
Abstract Electron heat flux is an important value for ionospheric space weather modeling networks. Utilizing the 2D array of Time History of Events and Macroscale Interactions during Substorms all‐sky‐imager (ASI) observations, Gabrielse et al. (2021, https://doi.org/10.3389/fphy.2021.744298 ) described a new method that estimates the auroral scale sizes of intense precipitating electron energy fluxes and their mean energies during two substorms on 16 February 2010. These parameters in combination with SuperThermal Electron Transport code were used to develop a new methodology to calculate electron thermal fluxes from data inputs in 2D during one of the substorms at 09:40:00 UT across Canada and Alaska. To test the effect of various precipitation lifetimes on electron heat flux values, boxcar averages ranging from 0 to 900 s were applied to the ASI data. These data are then combined with the newly developed kinetic simulation to determine the thermal fluxes associated with the observed diffuse and discrete precipitation.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".