Alignment in star–debris disc systems seen by <i>Herschel</i>
Bibliographic record
Abstract
Abstract Many nearby main-sequence stars have been searched for debris using the far-infrared Herschel satellite, within the DEBRIS, DUNES and Guaranteed-Time Key Projects. We discuss here 11 stars of spectral types A–M where the stellar inclination is known and can be compared to that of the spatially resolved dust belts. The discs are found to be well aligned with the stellar equators, as in the case of the Sun's Kuiper belt, and unlike many close-in planets seen in transit surveys. The ensemble of stars here can be fitted with a star–disc tilt of ≲ 10°. These results suggest that proposed mechanisms for tilting the star or disc in fact operate rarely. A few systems also host imaged planets, whose orbits at tens of au are aligned with the debris discs, contrary to what might be expected in models where external perturbers induce tilts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".