Petrographic observations and evaporate mound analysis of quartz-hosted fluid inclusions hosted by granitoid samples from the South Mountain Batholith, Nova Scotia: an exploration tool for vectoring towards mineralised areas in intrusive rocks
Bibliographic record
Abstract
The ca. 380 Ma South Mountain Batholith (SMB) of Nova Scotia is a large (ca. 7,300 km2), mesozonal granitoid intrusion that consists of 13 coalesced plutons of granodiorite to leucomonzogranitic composition which host a variety of mineralised zones (e.g., Sn-Zn-Cu-Ag, Mo, Mn-Fe-P, U, Cu-Ag). Given the hydrothermal nature of this mineralisation, it is expected that a fingerprint of the mineralizing fluids might be manifested both petrographically and by the chemistry of secondary, quartz-hosted fluid inclusions in the granites on a scale equal to or larger than the mineralised centres. In order to assess the potential of using the petrographic and chemical fingerprints as vector for exploration, a study integrating both these methods was investigated. The protocol involved in the study included the following: (1) completing a detailed petrographic study of hundreds of archived thin section samples that focused on the extent and degree of alteration that reflect fluid-rock interaction. The indices included: (i) type and abundance of perthite, (ii) chloritic alteration of biotite, (iii) plagioclase alteration, (iv) amount of secondary white mica, and (v) abundance of secondary fluid inclusions in quartz; and (2) determining the fluid chemistry of quartzhosted fluid inclusions in samples (n = 66) collected from the SMB. For this study, a detailed protocol was developed to address specific analytical considerations, including decrepitation temperature, oven versus stage heating, EDS calibration, EDS acquisition time, representative sampling and raster versus point mode of analysis. Thus, in this study, quartz chips were heated to 500ºC and a maximum of 16 mounds per sample were analysed (60 seconds) in raster mode, the latter to circumvent chemical variation related to elemental fractionation during mound formation. To date, the results indicate that the fluids from Phase 1 samples are dominated by a Na-F-Cl-Ca fluid. In contrast, fluids from Phase 2 samples are dominated by two fluid inclusion populations: a Na-K fluid and a F-Na-Cl-Ca fluid.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".