Bibliographic record
Abstract
Clinopyroxenes are among the first minerals to crystallize out of a ferromagnesian silicate magma. They commonly exhibit “sectorzoning”, a phenomenon whereby the crystal incorporates elements in different proportions on non-equivalent crystal faces. By growing clinopyroxene crystals in the laboratory, it is possible to investigate controls on compositional variation, which provides insight on magmatic processes. The goal of this research was to develop an experimental method for growing synthetic clinopyroxene (a silicate mineral) in a carbonate melt rather than in a silicate one. This is advantageous since silicate residue on the clinopyroxene crystal may damage crystal faces, which contain important information on growth features, unlike carbonate residue which is easily dissolved leaving crystal faces intact. The carbonate melt was modeled after the alkali-rich carbonatite lavas erupting at Oldoinyo Lengai, Tanzania by using powdered clinopyroxene, magnetite and alkali carbonates containing up to 5% wt. water as starting materials, and running the experiment at conditions of 800∞C and 10 kbars. Clinopyroxene crystals in a carbonate crystalline matrix were retrieved from the experiment capsules, and cleaned for imaging and analysis with the atomic force microscope (AFM), scanning electron microscope (SEM) and electron microprobe (EMP). This experimental approach provides well-preserved crystal faces whose surfaces can be examined at nanoscale resolution. This technique could be applied to a wide range of synthetic silicate minerals, and the resulting observations help to better understand the relationship between crystal surface structure and trace element uptake during crystal growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.072 |
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".