TOI-674b: An oasis in the desert of exo-Neptunes transiting a nearby M dwarf
Bibliographic record
Abstract
Context. The NASA mission TESS is currently doing an all-sky survey from space to detect transiting planets around bright stars. As part of the validation process, the most promising planet candidates need to be confirmed and characterized using follow-up observations. Aims. In this article, our aim is to confirm the planetary nature of the transiting planet candidate TOI-674b using spectroscopic and photometric observations. Methods. We use TESS, Spitzer, ground-based light curves, and HARPS spectrograph radial velocity measurements to establish the physical properties of the transiting exoplanet candidate TOI-674b. We perform a joint fit of the light curves and radial velocity time series to measure the mass, radius, and orbital parameters of the candidate. Results. We confirm and characterize TOI-674b, a low-density super-Neptune transiting a nearby M dwarf. The host star (TIC 158588995, V = 14.2 mag, J = 10.3 mag) is characterized by its M2V spectral type with M⋆ = 0.420 ± 0.010 M⊙, R⋆ = 0.420 ± 0.013 R⊙, and Teff = 3514 ± 57 K; it is located at a distance d = 46.16 ± 0.03 pc. Combining the available transit light curves plus radial velocity measurements and jointly fitting a circular orbit model, we find an orbital period of 1.977143 ± 3 × 10−6 days, a planetary radius of 5.25 ± 0.17 R⊕, and a mass of 23.6 ± 3.3 M⊕ implying a mean density of ρp =0.91 ± 0.15 g cm−3. A non-circular orbit model fit delivers similar planetary mass and radius values within the uncertainties. Given the measured planetary radius and mass, TOI-674b is one of the largest and most massive super-Neptune class planets discovered around an M-type star to date. It is found in the Neptunian desert, and is a promising candidate for atmospheric characterization using the James Webb Space Telescope.
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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 | 0.001 | 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".