An Investigation of the Geochemistry and Hydrogeology of the Queen Charlotte Fault
Bibliographic record
Abstract
Considerable attention has been given to characterizing the relationship between fluids and plate boundary fault systems at convergent margins, yet comparatively little is known about the hydrogeology of submerged transform boundaries. Following the 2012 M7.8 earthquake off western Haida Gwaii, an international scientific partnership was established between US and Canadian scientists to study the Queen Charlotte Fault – a ~1200 km transform fault between the Pacific and North American plates, where ~ 900 km lies offshore. Scientific expeditions onboard the R/V John P. Tully in 2015 and 2017 identified numerous water column anomalies (i.e seeps), mud volcanoes, microbial mats, and indicators of seabed fluid flow along the QCF. Analyses of pore fluids recovered from the 2017 cruise revealed abundant overprinting signatures of carbonate precipitation, anaerobic oxidation of methane, and particulate organic carbon sulfate reduction processes that dictate the chemistry of the observed pore waters. These chemical processes promote the formation of carbonates and iron sulfides that fuel microbial mats and diverse chemosynthetic communities at the seafloor. Analyses of water isotopes and chloride concentrations suggest that certain locations in proximity to the QCF may be influenced by meteoric water, or some currently unknown isotopic depletion process. Strontium isotopes reveal a non-radiogenic strontium signature at depth, suggesting basalt-fluid interaction and/or a diagenetic overprinting of sedimentary ash alteration. Fluids collected from CTD casts in the southern portion of the QCF suggest that actively seeping fluids have been influenced by the formation of gas hydrates. Taken together, the results presented in this investigation imply a significant flux of hydrocarbons (primarily methane) is occurring from buried sediments, in combination with high productivity in the water column contributing organic material during sedimentation. A general overall signature of authigenic carbonate precipitation is found at most sites along the entire length of the QCF, acting as a major sink for calcium, magnesium, and strontium between the ocean and seafloor sediments. Migration of fluids within the QCF is complex and varied from the northern region to the south – this study provides an overall preliminary insight to the inner workings of the QCF that merit ongoing investigation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".