174P/Echeclus and Its Blue Coma Observed Post-outburst
Bibliographic record
Abstract
Abstract It has been suggested that centaurs may lose their red surfaces and become bluer due to the onset of cometary activity, but the way in which cometary outbursts affect the surface composition and albedo of active centaurs is poorly understood. We obtained consistent visual-near-infrared (VNIR) reflectance spectra of the sporadically active centaur 174P/Echeclus during a period of inactivity in 2014 and six weeks after its outburst in 2016 to see if activity had observably changed the surface properties of the nucleus. We observed no change in the surface reflectance properties of Echeclus following the outburst compared to before, indicating that, in this case, any surface changes due to cometary activity were not sufficiently large to be observable from Earth. Our spectra and post-outburst imaging have revealed, however, that the remaining dust coma is not only blue compared to Echeclus, but also bluer than solar, with a spectral gradient of −7.7 ± 0.6% per 0.1 μm measured through the 0.61–0.88 μm wavelength range that appears to continue up to λ ∼ 1.3 μm before becoming neutral. We conclude that the blue visual color of the dust is likely not a scattering effect, and instead may be indicative of the dust’s carbon-rich composition. Deposition of such blue, carbon-rich, comatic dust onto a red active centaur may be a mechanism by which its surface color could be neutralized.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".