Simulated mass measurements of the young planet K2-33b
Bibliographic record
Abstract
In this paper, we carry out simulations of radial velocity (RV) measurements of the mass of the 8-11 Myr Neptune-sized planet K2-33b using high-precision near infrared velocimeters like SPIRou at the Canada-France-Hawaii Telescope. We generate a RV curve containing a planet signature and a realistic stellar activity signal, computed for a central wavelength of 1.8 $μ$m and statistically compatible with the light-curve obtained with K2. The modelled activity signal includes the effect of time-evolving dark and bright surface features hosting a 2 kG radial magnetic field, resulting in a RV signal of semi-amplitude ~30 m/s. Assuming a 3-month visibility window, we build RV time-series including Gaussian white noise from which we retrieve the planet mass while filtering the stellar activity signal using Gaussian Process Regression. We find that 35/50 visits spread over 3 consecutive bright-time runs on K2-33 allow one to reliably detect planet RV signatures of respectively 10 and 5 m/s at precisions larger than 3 $σ$. We also show that 30 visits may end up being insufficient in some cases to provide a good coverage of the stellar rotation cycle, with the result that the planet signature can go undetected or the mass estimation be plagued by large errors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".