GAS EMISSION FROM DEBRIS DISKS AROUND A AND F STARS
Bibliographic record
Abstract
Gas has been detected in a number of debris disk systems. This gas may have arisen from grain sublimation or grain photodesorption. It interacts with the surrounding dust grains through a number of charge and heat exchanges. Studying the chemical composition and physical state of this gas can therefore reveal much about the dust component in these debris disks. We have produced a new code, ontario , to address gas emission from dusty gas-poor disks around A–F stars. This code computes the gas ionization and thermal balance self-consistently, with particular care taken of heating/cooling mechanisms. Line emission spectra are then produced for each species (up to zinc) by statistical equilibrium calculations of the atomic/ionic energy levels. For parameters that resemble the observed β Pictoris gas disk, we find that the gas is primarily heated by photoelectric emission from dust grains, and primarily cooled through the C ii 157.7 μm line emission. The gas can be heated to a temperature that is warmer than that of the dust and may in some cases reach temperature for thermal escape. The dominant cooling line, C ii 157.7 μm, should be detectable by Herschel in these disks, while the O i 63.2 μm line will be too faint. We also study the dependence of the cooling line fluxes on a variety of disk parameters, in light of the much improved sensitivity to thermal line emission in the mid/far-infrared and at submillimeter wavelengths provided by, in particular, Herschel , SOFIA , and ALMA . These new instruments will yield much new information about dusty debris disks.
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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 | 0.000 | 0.000 |
| 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".