Validation of 13 Hot and Potentially Terrestrial TESS Planets
Bibliographic record
Abstract
Abstract The James Webb Space Telescope will be able to probe the atmospheres and surface properties of hot, terrestrial planets via emission spectroscopy. We identify 18 potentially terrestrial planet candidates detected by the Transiting Exoplanet Survey Satellite (TESS) that would make ideal targets for these observations. These planet candidates cover a broad range of planet radii (R p ∼ 0.6–2.0R ⊕) and orbit stars of various magnitudes (K s = 5.78–10.78, V = 8.4–15.69) and effective temperatures (T eff ∼ 3000–6000 K). We use ground-based observations collected through the TESS Follow-up Observing Program (TFOP) and two vetting tools—DAVE and TRICERATOPS—to assess the reliabilities of these candidates as planets. We validate 13 planets: TOI-206 b, TOI-500 b, TOI-544 b, TOI-833 b, TOI-1075 b, TOI-1411 b, TOI-1442 b, TOI-1693 b, TOI-1860 b, TOI-2260 b, TOI-2411 b, TOI-2427 b, and TOI-2445 b. Seven of these planets (TOI-206 b, TOI-500 b, TOI-1075 b, TOI-1442 b, TOI-2260 b, TOI-2411 b, and TOI-2445 b) are ultra-short-period planets. TOI-1860 is the youngest (133 ± 26 Myr) solar twin with a known planet to date. TOI-2260 is a young (321 ± 96 Myr) G dwarf that is among the most metal-rich ([Fe/H] = 0.22 ± 0.06 dex) stars to host an ultra-short-period planet. With an estimated equilibrium temperature of ∼2600 K, TOI-2260 b is also the fourth hottest known planet with R p < 2 R ⊕.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".