Supplementary Information for "Underplated melts control sulfide segregation at the continental crust-mantle transition"
Bibliographic record
Abstract
This repository contains the supplementary materials for "Underplated melts control sulfide segregation at the continental crust-mantle transition". Contained within:Supplementary figuresSupplementary Table 1. Nomenclature of the samples collected from the Balmuccia mantle peridotites, Contact Series sequence, and Mafic Complex with the corresponding numbers of thin-sections and whole-rock analyses number used in this study.Suplementary Table 2. Bulk-rock chemical composition of the investigated samples.Supplementary Table 3. Petrographic and textural characteristics of sulfides.Supplementary Table 4. Average major and trace element composition of pentlandites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 5. Average major and trace element composition of pyrrhotites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 6. Average major and trace element composition of chalcopyrites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 7. Average major and trace element composition of pyrites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 8. Average major element contents (wt%) and their molar ratios in sulfide phases.Supplementary Table 9. Bulk sulfur geochemistry of the Contact Series sequence of the Balmuccia peridotite massif.Supplementary Table 10. Detection limits and uncertainties of the whole-rock major element measurements determined using X-ray Fluorescence at the Federal Institute for Geosciences and Natural Resources (BGR), Hannover, Germany.Supplementary Table 11. Detection limits and uncertainties for selected elements of the whole-rock trace element measurements at the Activation Laboratories Ltd., Canada.Supplementary Table 12. Modal composition of host silicate rocks.Supplementary Table 13. Detection limit (ppm), accuracies (%), and precisions (rel.%) of EPMA measurements for sulfides.Supplementary Table 14. The accuracy and precision of the LA-ICP-MS measurements calculated based on Se and Rh contained in both NIST 610 and PGE-A standards. The normalization values are adapted from Lorand and Alard (2001).Supplementary Table 15. Average detection limits and sample errors (ppm) of LA-ICPMS measurements for pentlandites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 16. Average detection limits and sample errors (ppm) of LA-ICPMS measurements for pyrrhotites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 17. Average detection limits and sample errors (ppm) of LA-ICPMS measurements for chalcopyrites from Balmuccia mantle peridotites and Contact Series sequence.Supplementary Table 18. Average detection limits and sample errors (ppm) of LA-ICPMS measurements for pyrites from Balmuccia mantle peridotites and Contact Series sequence.In addition to supplementary materials, associated with the submission to Communications Earth & Environment, this repository contains raw data collected during electron microprobe measurements (EPMA) and laser ablation coupled to inductively coupled plasma mass spectrometry (LA-ICPMS) measurements. The original files of LA-ICPMS measurements are packed into one folder entitled "LA_ICPMS_raw data" and grouped into analytical sessions (each session per one thin-section). The LA-ICPMS results are associated with EPMA results, as the same sulfide grains have been analyzed by these two methods.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.801 | 0.430 |
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".