SPATIALLY RESOLVED IMAGING OF THE TWO-COMPONENT η Crv DEBRIS DISK WITH<i>HERSCHEL</i>
Bibliographic record
Abstract
We present far-infrared and submillimeter images of the η Crv debris disk system obtained with Herschel and SCUBA-2, as well as Hubble Space Telescope visible and near-infrared coronagraphic images. In the 70 μm Herschel image, we clearly separate the thermal emission from the warm and cold belts in the system, find no evidence for a putative dust population located between them, and precisely determine the geometry of the outer belt. We also find marginal evidence for azimuthal asymmetries and a global offset of the outer debris ring relative to the central star. Finally, we place stringent upper limits on the scattered light surface brightness of the outer ring. Using radiative transfer modeling, we find that it is impossible to account for all observed properties of the system under the assumption that both rings contain dust populations with the same properties. While the outer belt is in reasonable agreement with the expectations of steady-state collisional cascade models, albeit with a minimum grain size that is four times larger than the blow-out size, the inner belt appears to contain copious amounts of small dust grains, possibly below the blow-out size. This suggests that the inner belt cannot result from a simple transport of grains from the outer belt and rather supports a more violent phenomenon as its origin. We also find that the emission from the inner belt has not declined over three decades, a much longer timescale than its dynamical timescale, which indicates that the belt is efficiently replenished.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".