The Ophiuchus DIsc Survey Employing ALMA (ODISEA) – I: project description and continuum images at 28 au resolution
Bibliographic record
Abstract
We introduce the Ophiuchus DIsc Survey Employing ALMA (ODISEA), a project aiming to study the entire population of Spitzer-selected protoplanetary discs in the Ophiuchus Molecular Cloud (∼300 objects) from both millimetre continuum and CO isotopologues data. Here we present 1.3 mm/230 GHz continuum images of 147 targets at 0.2 arcsec (28 au) resolution and a typical rms of 0.15 mJy. We detect a total of 133 discs, including the individual components of 11 binary systems and 1 triple system. 60 of these discs are spatially resolved. We find clear substructures (inner cavities, rings, gaps, and/or spiral arms) in eight of the sources and hints of such structures in another four discs. We construct the disc luminosity function for our targets and perform preliminary comparisons to other regions. A simple conversion between flux and dust mass (adopting standard assumptions) indicates that all discs detected at 1.3 mm are massive enough to form one or more rocky planets. In contrast, only ∼50 discs (∼1/3 of the sample) have enough mass in the form of dust to form the canonical 10 M⊕ core needed to trigger runaway gas accretion and the formation of gas giant planets, although the total mass of solids already incorporated into bodies larger than cm scales is mostly unconstrained. The distribution in continuum disc sizes in our sample is heavily weighted towards compact discs: most detected discs have radii < 15 au, while only 23 discs (|${\sim }15{{\ \rm per\ cent}}$| of the targets) have radii > 30 au.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".