The Origins of Lithium Enhancement in Polluted White Dwarfs
Bibliographic record
Abstract
The bulk abundances of exoplanetesimals can be measured when they are accreted by white dwarfs. Recently, lithium from the accretion of exoplanetesimals was detected in relatively high levels in multiple white dwarfs. There are presently three proposed hypotheses to explain the detection of excess lithium in white dwarf photospheres: Big Bang and Galactic nucleosynthesis, continental crust, and an exomoon formed from spalled ring material. We present new observations of three previously known lithium-polluted white dwarfs (WD J1824+1213, WD J2317+1830, and LHS 2534), and one with metal pollution without lithium (SDSS J1636+1619). We also present atmospheric model fits to these white dwarfs. We then evaluate the abundances of these white dwarfs and two additional lithium-polluted white dwarfs that were previously fit using the same atmospheric models (WD J1644$-$0449 and SDSS J1330+6435) in the context of the three extant hypotheses for explaining lithium excesses in polluted white dwarfs. We find Big Bang and Galactic nucleosynthesis to be the most plausible explanation of the abundances in WD J1644$-$0449, WD J1824+1213, and WD J2317+1830. SDSS J1330+6435 will require stricter abundances to determine its planetesimal's origins, and LHS 2534, as presently modeled, defies all three hypotheses. We find the accretion of an exomoon formed from spalled ring material to be highly unlikely to be the explanation of the lithium excess in any of these cases.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".