<i>Euclid</i>: Early Release Observations – A glance at free-floating newborn planets in the σ Orionis cluster
Bibliographic record
Abstract
We provide an early assessment of the imaging capabilities of the Euclid space mission to deeply probe nearby star-forming regions and associated very young open clusters, and in particular, to determine to which extent it can shed light into the newborn free- floating planet population. This paper focusses on a low-reddening region observed in just one Euclid pointing. The dust and gas has been cleared out from the region by the hot σ Orionis star. One late-M and six known spectroscopically confirmed L-type ultracool members in the σ Orionis cluster were used as benchmarks to provide a high-purity procedure to select new candidate members with Euclid. The exquisite angular resolution and depth delivered by the Euclid instruments allowed us to focus on bona fide point sources. A cleaned sample of σ Orionis cluster substellar members was produced, and the initial mass function (IMF) was estimated by combining Euclid and Gaia data. Our σ Orionis substellar IMF is consistent with a power-law distribution without a significant steepening at the planetary-mass end. No evidence of a low-mass cutoff is found down to the detection limit of this study at 4 Jupiter masses in the very young σ Orionis open cluster.
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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".