Breaking Degeneracies in Formation Histories by Measuring Refractory Content in Gas Giants
Bibliographic record
Abstract
Abstract Relating planet formation to atmospheric composition has been a long-standing goal of the planetary science community. So far, most modeling studies have focused on predicting the enrichment of heavy elements and the C/O ratio in giant planet atmospheres. Although this framework provides useful constraints on the potential formation locations of gas giant exoplanets, carbon and oxygen measurements alone are not enough to determine where a given gas giant planet originated. Here, we show that characterizing the abundances of refractory elements (e.g., silicon and iron) can break these degeneracies. Refractory elements are present in the solid phase throughout most of the disk, and their atmospheric abundances therefore reflect the solid-to-gas accretion ratio during formation. We introduce a new framework that parameterizes the atmospheric abundances of gas giant exoplanets in the form of three ratios: Si/H, O/Si, and C/Si. Si/H traces the solid-to-gas accretion ratio of a planet and is loosely equivalent to earlier notions of “metallicity.” For O/Si and C/Si, we present a global picture of their variation with distance and time based on what we know from the solar system meteorites and an updated understanding of the variations of thermal processing within protoplanetary disks. We show that ultrahot Jupiters are ideal targets for atmospheric characterization studies using this framework as we can measure the abundances of refractories, oxygen, and carbon in the gas phase. Finally, we propose that hot Jupiters with silicate clouds and low water abundances might have accreted their envelopes between the soot line and the water snow line.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".