Electron microprobe analyses of quenched melts (now glass), chromite, and olivine to determine the role of contamination on chromite crystallization in ultramafic magmas
Bibliographic record
Abstract
The data were generated in two labotories of the Dalhousie University in Halifax during a series of experiments to determine the solubility of chromite in komatiite mixed with different crustal contaminants. The experiments were designed to determine the solubility of the mineral chromite in silicate melt, with the dominant variable being the silica and iron content of the melt. After equilibrating chromite with melt at 1192-1430 degrees Celcius, samples were quenched and the composition of the chromite, quenched melt (now glass), and olivine run-products were measured for major and minor elements by electron microprobe, and the chromium concentration in the glass was measured by laser ablation ICP-MS. Analytical procedures are included in the associated data description file. The data are provided in a series of Excel worksheets containing five data tables. Table 1 is a summary of the composition of the starting materials used in experiments. Table 2 is a summary of the conditions of temperature, oxygen fugacity, experiment duration and initial sample composition. Table 3 is a summary of the major and minor element composition of the glass measured by electron microprobe and laser ablation ICP-MS. Tables 4 and 5 are summaries of the major and minor element composition of the olivine and chromite, respectively, measured by electron microprobe.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.017 |
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".