DOES THE PRESENCE OF PLANETS AFFECT THE FREQUENCY AND PROPERTIES OF EXTRASOLAR KUIPER BELTS? RESULTS FROM THE<i>HERSCHEL</i>DEBRIS AND DUNES SURVEYS
Bibliographic record
Abstract
The study of the planet-debris disk connection can shed light on the formation and evolution of planetary systemsand may help "predict" the presence of planets around stars with certain disk characteristics.In preliminary analyses of subsamples of the Herschel DEBRIS and DUNES surveys, Wyatt et al. and Marshall et al. identified a tentative correlation between debris and the presence of low-mass planets.Here we use the cleanest possible sample out of these Herschel surveys to assess the presence of such a correlation, discarding stars without known ages, with ages <1 Gyr, and with binary companions <100 AUto rule out possible correlations due to effects other than planet presence.In our resulting subsample of 204 FGK stars, we do not find evidence that debris disks are more common or more dusty around stars harboring high-mass or low-mass planets compared to a control sample without identified planets.There is no evidence either that the characteristic dust temperature of the debris disks around planet-bearing stars is any different from that in debris disks without identified planets, nor that debris disks are more or less common (or more or less dusty) around stars harboring multiple planets compared to singleplanet systems.Diverse dynamical histories may account for the lack of correlations.The data show a correlation between the presence of high-mass planets and stellar metallicity, but no correlation between the presence of lowmass planets or debris and stellar metallicity.Comparing the observed cumulative distribution of fractional luminosity to those expected from a Gaussian distribution in logarithmic scale, we find that a distribution centered on the solar system's value fits the data well, while one centered at 10 times this value can be rejected.This is of interest in the context of future terrestrial planet detection and characterization because it indicates that there are good prospects for finding a large number of debris disk systems (i.e., with evidence of harboring planetesimals, the building blocks of planets) with exozodiacal emission low enough to be appropriate targets for an ATLASTtype mission to search for biosignatures.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".