An ALMA 1.3 millimeter Search for Debris Disks around Solar-type Stars in the Pleiades
Bibliographic record
Abstract
Abstract Millimeter emission from debris disks around stars of different ages provides constraints on the collisional evolution of planetesimals. We present ALMA 1.3 millimeter observations of a sample of 76 Solar-type stars in the ∼115 Myr old Pleiades star cluster. These ALMA observations complement previous infrared observations of this sample by providing sensitivity to emission from circumstellar dust at lower temperatures, corresponding to debris at radii comparable to the Kuiper Belt and beyond. The observations obtain a beam size of 1.″5 (200 au) and a median rms noise of 54 μJy beam−1, which corresponds to a fractional luminosity L dust/L star ∼ 10−4 for 40 K dust for a typical star in the sample. The ALMA images show no significant detections of the targeted stars. We interpret these limits in the context of a steady-state collisional cascade model for debris disk evolution that provides a good description of observations of the field population near the Sun but is not well-calibrated on younger populations. The ALMA nondetections of the Pleiades systems are compatible with the disk flux predictions of this model. We find no high fractional luminosity outliers from these ALMA data that could be associated with enhanced collisions resulting from activity not accounted for by steady-state evolution. However, we note that two systems (H ii 1132 and HD 22680) show 24 μm excess much higher than the predictions of this model, perhaps due to unusually high dust production from dynamical events involving planets.
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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 | 0.001 |
| 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".