WEATHER ON OTHER WORLDS. I. DETECTION OF PERIODIC VARIABILITY IN THE L3 DWARF DENIS-P J1058.7-1548 WITH PRECISE MULTI-WAVELENGTH PHOTOMETRY
Bibliographic record
Abstract
Photometric monitoring from warm Spitzer reveals that the L3 dwarf DENIS-P J1058.7-1548 varies sinusoidally in brightness with a period of hr and an amplitude of 0.388% ± 0.043% (peak-to-valley) in the 3.6 μm band, confirming the reality of a 4.31 ± 0.31 hr periodicity detected in J -band photometry from the SOAR telescope. The J -band variations are a factor of 2.17 ± 0.35 larger in amplitude than those at 3.6 μm, while 4.5 μm Spitzer observations yield a 4.5 μm/3.6 μm amplitude ratio of only 0.23 ± 0.15, consistent with zero 4.5 μm variability. This wide range in amplitudes indicates rotationally modulated variability due to magnetic phenomena and/or inhomogeneous cloud cover. Weak Hα emission indicates some magnetic activity, but it is difficult to explain the observed amplitudes by magnetic phenomena unless they are combined with cloud inhomogeneities (which might have a magnetic cause). However, inhomogeneous cloud cover alone can explain all our observations, and our data align with theory in requiring that the regions with the thickest clouds also have the lowest effective temperature. Combined with published v sin ( i ) results, our rotation period yields a 95% confidence lower limit of R * ⩾ 0.111 R ☉ , suggesting upper limits of 320 Myr and 0.055 M ☉ on the age and mass. These limits should be regarded cautiously because of ∼3σ inconsistencies with other data; however, a lower limit of 45° on the inclination is more secure. DENIS-P J1058.7-1548 is only the first of nearly two dozen low-amplitude variables discovered and analyzed by the Weather on Other Worlds project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".