Major and minor element compositions of ocean island olivine and spinel
Bibliographic record
Abstract
The dataset consists of elemental compositions determined for olivine and spinel from 15 ocean islands, including Azores, Austral, Balleny, Cape Verde, Crozet, Fernando de Noronha, Galapagos, Gough, Juan Fernandez, Marquesas, Réunion, Society, St. Helena, Trindade, and Tristan da Cunha. These samples were loaned from Sedgwick Museum, University of Cambridge and National History Museum, London, except the Galapagos samples provided by D. Geist and the Réunion (Piton de la Fournaise) samples provided by J. Maclennan. Elemental compositions determined for three secondary standards (San Carlos olivine, MongOl olivine, and NHNM164905 augite) are also presented in the dataset. The data were acquired using a Cameca SX100 electron microscope at the Department of Earth Sciences, University of Cambridge, in four sessions between June and November 2021. The elements analysed include Mg, Si, Fe, Al, Ca, P, Cr, Mn, and Ni in olivine, and Mg, Si, Fe, Al, Ca, Cr, Mn, and Ti in spinel. The data were used to calculate olivine crystallisation temperatures and mantle potential temperatures based on an olivine-spinel thermometer and modelling of mantle melting. The data for olivine and spinel are presented separately in two spreadsheets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".