Lithium Isotopic Signature of Hawaiian Basalts
Bibliographic record
Abstract
R ecycling of oceanic crust and sediment is a common mechanism to account for the presence of chemical heterogeneities observed in oceanic island basalts (OIBs). Because of the sizeable fractionation of lithium isotopes in low‐temperature environments, lithium serves as a tracer for recycled material in OIB sources. In this study, we analyzed 88 samples of Hawaiian basalt from all volcanic stages and 10 samples of altered oceanic crust from Ocean Drilling Program (ODP) Site 843 for lithium isotopes. The measured range of lithium isotopes is δ 7 Li = 0.8‰ –5.7‰. Corr elations of lithium isotopes with radiogenic isotopes indicate lithium isotopes may be used to trace mantle sources in Hawaiian lavas. Loa trend shield volcanoes appear to show lower δ 7 Li, differentiating between the Loa and Kea geochemical trends. Similarly, postshield lavas have lower δ 7 Li than shield lavas. In Hawaiian basalts, lithium isotopes help distinguish between Loa source components: Ko‘olau Makapu‘u shield stage lavas may have between 1% and 5% of a carbonate input and Hualālai postshield and shield lavas may reflect incorporation of subduction eroded lower continental crust. Comparison of this data set with worldwide OIB published lithium isotopic data indicates that the lithium isotopic system behaves systematically on a mantlewide scale.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".