Bibliographic record
Abstract
The prototype of an auroral colour camera named Rainbow was run at the Auroral Station in Adventdalen, Svalbard, Norway, during a Finnish optical campaign in February, 2004. Instead of narrow band-pass filters and grey-scale images, this imager records colour images of the aurora using four wide-band channels (a colour CCD) with the field-of-view of about 150°. In this study, we show the results of fitting the four Rainbow channels (cyan-magenta, cyan-green, yellow-magenta, yellow-green) to reconstruct the traditionally filtered auroral wavelengths: green (557.7 nm), red (630.0 nm), and blue (427.8 nm), which were simultaneously recorded by the meridian scanning photometer (MSP) at the same station. This fit is qualitatively extremely good and almost linear throughout the data. In studying the auroral evolution during substorms, there is no significant difference whether MSP or Rainbow data are used. However, due to wide-band colour channels, the background illumination has a strong effect on the Rainbow data. During low signal levels (only background or faint aurora) the reconstruction errors are larger. The data for this study were captured on 21 February 2004. The time period of interest includes a substorm sequence, which is examined using colour auroral images and data from the MSP. PACS No.: 94.20.Ac
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".