Taking the Temperature of Hydrothermal Ore Deposits Using Clumped Isotope Thermometry
Bibliographic record
Abstract
Abstract Better tools are needed to map the thermal structure of ore deposits. Here, carbonate clumped isotope thermometry is applied for the first time in epithermal, skarn, and carbonate-hosted deposits to identify the conditions involved in metal transport and deposition. Clumped isotope temperature calibrations were tested by measurement of carbonates from three geothermal fields in the Taupo volcanic zone, New Zealand, that record growth temperatures between 130° and 310°C. Results for modern Taupo volcanic zone calcites were paired with known fluid δ18O values and these indicate precipitation in equilibrium with produced geothermal waters. Measurements carried out at the Waihi low sulfidation deposit in New Zealand, the Antamina polymetallic skarn in Peru, and the Mount Isa sediment hosted Pb-Zn and Cu deposit in Queensland, Australia, demonstrate that clumped isotope values are sensitive to temperature gradients defined using other methods. At Waihi, an andesite-hosted deposit, temperature controls the majority of variation in carbonate mineral δ18O. At Mount Isa, ~300° to 400°C temperatures were recorded in a 1.5 Ga orebody, which are consistent with fluid inclusion values, highlighting the longevity of clumped isotope archives in dolomite minerals. Collectively, these results demonstrate the potential for clumped isotopes to delineate the heat footprint around deposits that contain carbonates, and to more effectively disentangle magmatic and meteoric fluid δ18O signals.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".