BROMINE IN SCAPOLITE-GROUP MINERALS AND SODALITE: XRF MICROPROBE ANALYSIS, EXCHANGE EXPERIMENTS, AND APPLICATION TO SKARN DEPOSITS
Bibliographic record
Abstract
Application of an X-ray fluorescence (XRF) microprobe for the analysis of single grains (80 to 1,000 m in diameter) of Cl-rich minerals for Br has been evaluated for fluorapatite, chlorapatite, scapolite-group minerals (marialite and meonite) and sodalite. A calibration curve based on the Br contents in four international reference materials has been confirmed by measurements on Br-bearing standard solutions and by agreement with the results of Cl-rich minerals from instrumental neutron-activation analyses. Absolute errors associated with individual XRF microprobe analyses (i.e., counting statistics alone) are less than 5%, and the calculated limit of detection in the analysis of single mineral grains is ~1 ppm Br. Matrix and grain-size effects are shown to be negligible. Experiments at 1 atmosphere and 800 to 1000°C yield the following distribution coefficients for Br–Cl exchanges between marialite or sodalite and hydrous NaCl–NaBr melts: KDmarialite–melt = 0.97 ± 0.08 and KDsodalite–melt = 0.9 ± 0.1. Therefore, the Cl/Br values in marialite and sodalite closely reflect the halogen proportions of their coexisting melts or fluids. The diffusivity of Br in sodalite follows an Arrhenius relation: DBr = 6.5 10–7 exp(–270 ± 10kJ/mol/RT) m2/s, over the temperature range from 800 to 1000°C. DBr in marialite is 1.7 ± 0.3 10–19 m2/s at 800°C. The Cl/Br weight ratios of marialite in the Tieshan Fe skarn deposit, China, cluster around 650 ± 40, supporting an origin involving hydrothermal brines from associated evaporites. Scapolite-group minerals in the exoskarns of the Nickel Plate Au skarn deposit, British Columbia, have Cl/Br from 560 to 570, higher than those (130 to 180) of their counterparts in the endoskarns and vuggy cavities. This variation is attributable to an increased
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".