Bibliographic record
Abstract
Detailed petrological, mineralogical and melt-inclusion studies of an unusual plagioclase-phyric high-Ca boninite from the North Tongan forearc demonstrate that phenocrysts of high-An plagioclase (An>90) crystallized at the latest stages of melt evolution from H2O-saturated dacitic melts (64-67 wt.% SiO2, ∼2 wt.% MgO) at ∼1050°C and low pressure (< 1 kbar). These melts contained ∼1.5 wt.% H2O and had low CaO/Na2O (∼3, in wt.%). Our results suggest that the presence of high-Ca (An>90) plagioclase phenocrysts in arc lavas does not necessarily imply either high H2O-contents of the melt (>6 wt.%), or involvement of refractory melts (CaO/Na2O > 8) in magma genesis, as was previously suggested. Established conditions of crystallization [P, T, X, X(H2O)] during evolution of the Tongan boninite contradict those predicted by available models of plagioclase-melt equilibria. The effect of H2O on the activities of plagioclase components in hydrous melts is strongly nonlinear. Extrapolation of experimental results on the effect of H2O on plagioclase-melt equilibria from melt H2O contents of >4 wt% to the low H2O contents (<2 wt%) of the evolved Tongan boninite predicts a less calcic plagioclase than observed, or higher H2O contents than measured in plagioclase-hosted melt inclusions. These observations are in accord with the well-known large effect of small amounts of H2O on mineral melting temperatures, and also with recent results on the effect of H2O on melt viscosities at low H2O contents. Better predictions require new experimental data at low P(H2O) (<1 kbar).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.991 | 0.994 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".