Constraints on the Origins of Fluids Forming Irish Zn-Pb-Ba Deposits: Evidence from the Composition of Fluid Inclusions
Bibliographic record
Abstract
The numerous Zn-Pb deposits in the Irish midlands, together with the quantity and grade of the ore, make this a world-class base metal province. Despite significant exploration and research, there is still disagreement on the origin of the mineralizing fluids. In this study, we have measured the composition of fluid inclusions using a crush-leach technique. These data constrain the possible sources of the fluids both during and after mineralization. Chloride and Br concentrations indicate that the main ore fluid at Tynagh and Silvermines was seawater that had evaporated until the salinity was between 12 and 18 wt percent. However, Na, K, and Li data show that water-rock interactions have resulted in the depletion of Na and the enrichment of K and Li relative to the concentrations expected for evaporated seawater. The fluids that produced postore dolomitization were also derived from seawater that had evaporated to higher salinities and had precipitated halite. The concentrations of Na, K, and Li are what would be expected for seawater at this degree of evaporation, and show that these fluids did not interact with the same lithologies as the ore fluids. The major change to their fluid composition was exchange of Mg for Ca during dolomitization. We suggest that the ore fluids could only have reached their high salinity by evaporation of seawater on the extensive shallow water shelf regions that existed over much of the Irish midlands.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".