Observations of the auroral width spectrum at kilometre-scale size
Bibliographic record
Abstract
Abstract. This study examines auroral colour camera data from the Canadian Dense Array Imaging SYstem (DAISY). The Dense Array consists of three imagers with different narrow (compared to all-sky view) field-of-view optics. The main scientific motivation arises from an earlier study by Knudsen et al. (2001) who used All-Sky Imager (ASI) combined with even earlier TV camera observations (Maggs and Davis, 1968) to suggest that there is a gap in the distribution of auroral arc widths at around 1 km. With DAISY observations we are able to show that the gap is an instrument artifact and due to limited spatial resolution and coverage of commonly used instrumentation, namely ASIs and TV cameras. If the auroral scale size spectrum is indeed continuous, the mechanisms forming these structures should be able to produce all of the different scale sizes. So far, such a single process has not been proposed in the literature and very few models are designed to interact with each other even though the range of their favourable conditions do overlap. All scale-sizes should be considered in the future studies of auroral forms and electron acceleration regions, both in observational and theoretical approaches.
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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 | 0.000 | 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".