PLANET TRAPS AND PLANETARY CORES: ORIGINS OF THE PLANET-METALLICITY CORRELATION
Bibliographic record
Abstract
Massive exoplanets are observed preferentially around high metallicity ([Fe/H]) stars while low-mass exoplanets do not show such an effect. This so-called planet–metallicity correlation generally favors the idea that most observed gas giants at r < 10 AU are formed via a core accretion process. We investigate the origin of this phenomenon using a semi-analytical model, wherein the standard core accretion takes place at planet traps in protostellar disks where rapid type I migrators are halted. We focus on the three major exoplanetary populations—hot Jupiters, exo-Jupiters located at r ≃ 1 AU, and the low-mass planets. We show using a statistical approach that the planet–metallicity correlations are well reproduced in these models. We find that there are specific transition metallicities with values [Fe/H] = −0.2 to −0.4, below which the low-mass population dominates, and above which the Jovian populations take over. The exo-Jupiters significantly exceed the hot Jupiter population at all observed metallicities. The low-mass planets formed via the core accretion are insensitive to metallicity, which may account for a large fraction of the observed super-Earths and hot-Neptunes. Finally, a controlling factor in building massive planets is the critical mass of planetary cores ( M c , crit ) that regulates the onset of rapid gas accretion. Assuming the current data is roughly complete at [Fe/H] > −0.6, our models predict that the most likely value of the "mean" critical core mass of Jovian planets is 〈 M c , crit 〉 ≃ 5 M ⊕ rather than 10 M ⊕ . This implies that grain opacities in accreting envelopes should be reduced in order to lower M c , crit .
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".