Let the Great World Spin: Revealing the Turbulent, Stormy Atmospheres of Giant Planet Analogs
Bibliographic record
Abstract
Photometric variability monitoring is sensitive to atmospheric features as they rotate in and out of view, allowing us to probe the presence of surface inhomogeneities caused by patchy clouds, hot spots and temperature fluctuations. Periodic variability has been detected in brown dwarfs with temperatures spanning 250 - 2200 K, and recently in a sample of free-floating, planetary-mass objects. These young, isolated, low-gravity objects share a striking resemblance with the directly-imaged planets and can be studied in far greater detail in the absence of a bright host star. The large amplitudes observed in this small sample of low-gravity objects suggests that variability may be enhanced for the exoplanet analogues. I will present results from a large Spitzer survey searching for variability in young, giant planet analogs, and discuss how these results reveal how the temperature, surface-gravity, rotation rate and inclination can influence observed variability properties.
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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 | 0.000 | 0.000 |
| 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".