DOES THE DEBRIS DISK AROUND HD 32297 CONTAIN COMETARY GRAINS?,
Bibliographic record
Abstract
We present an adaptive optics imaging detection of the HD 32297 debris disk at L ' (3.8 μm) obtained with the LBTI/LMIRcam infrared instrument at the Large Binocular Telescope. The disk is detected at signal-to-noise ratio per resolution element ∼3–7.5 from ∼0 3 to 1 1 (30–120 AU). The disk at L ' is bowed, as was seen at shorter wavelengths. This likely indicates that the disk is not perfectly edge-on and contains highly forward-scattering grains. Interior to ∼50 AU, the surface brightness at L ' rises sharply on both sides of the disk, which was also previously seen at Ks band. This evidence together points to the disk containing a second inner component located at ≲50 AU. Comparing the color of the outer (50 < r /AU <120) portion of the disk at L ' with archival Hubble Space Telescope /NICMOS images of the disk at 1–2 μm allows us to test the recently proposed cometary grains model of Donaldson et al. We find that the model fails to match this disk's surface brightness and spectrum simultaneously (reduced chi-square = 17.9). When we modify the density distribution of the model disk, we obtain a better overall fit (reduced chi-square = 2.87). The best fit to all of the data is a pure water ice model (reduced chi-square = 1.06), but additional resolved imaging at 3.1 μm is necessary to constrain how much (if any) water ice exists in the disk, which can then help refine the originally proposed cometary grains model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".