High-resolution ALMA observations of transition disk candidates in Lupus
Bibliographic record
Abstract
Transition disks with small inner dust cavities are interesting targets for the study of disk clearing mechanisms. Such disks have been identified through a deficit in the infrared part of their SED, but spatially resolved millimeter imaging is required to confirm the presence of an inner dust cavity. We use high-resolution ALMA observations of 30 mas resolution in Band 6 continuum and $^{12}$CO 2--1 emission of 10 transition disk candidates in the Lupus star forming region, in order to confirm the presence of inner dust cavities and infer the responsible mechanism. The continuum data are analyzed using visibility modeling and the SEDs are compared with radiative transfer models. Out of the six transition disk candidates selected from their SED, only one disk revealed an inner dust cavity of 4 au in radius. Three of the other disks are highly inclined, which limits the detectability of an inner dust cavity but it is also demonstrated to be the possible cause for the infrared deficit in their SED. The two remaining SED-selected disks are very compact, with dust radii of only $\sim$3 au. From the four candidates selected from low-resolution images, three new transition disks with large inner cavities $>$20 au are identified, bringing the total number of transition disks with large cavities in Lupus to 13. SED-selected transition disks with small cavities are biased towards highly inclined and compact disks, which casts doubt on the use of their occurrence rates in estimating dispersal timescales of photoevaporation. Using newly derived disk dust masses and radii, we re-evaluate the size-luminosity and $M_{\rm dust}-M_{\rm star}$ relations. These relations can be understood if the bright disks are dominated by disks with substructure whereas faint disks are dominated by drift-dominated disks. (Abridged)
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".