Bibliographic record
Abstract
Ductile shear zones are formed by tectonic plate interactions and are often thought to be deep-seated equivalents to faults. They can act as either barriers or conduits for fluid flow, and fluids can alter deformation mechanisms, metamorphic reactions, and strain accumulation in shear zones. Even though fluid is such an important factor in deformation, it is difficult to study due to its transient nature, so geochemical analyses may be used to interpret fluid conditions during deformation. The Seine River metaconglomerates in northwestern Ontario, Canada deformed and metamorphosed in a shear zone during an ancient microplate collision. They have clasts with varied lithology including felsic to ultramafic volcanic and granitoid clasts. Selected samples were previously analyzed to determine strain magnitudes by Czeck et al. (2009) who demonstrated that different clast types had differing rheologies that resulted in a range of strain magnitudes. Strain magnitude also varied across the region. Geochemical analysis and evaluation for fluid-rock interaction had not previously been performed on the Seine River metaconglomerates and was the focus of this study. Compositions of several clasts types were determined at a range of strain magnitudes using major and minor element X-Ray Fluorescence. Results from 33 analyses were reviewed to see if there were significant changes in composition from low to high deformation sites. Preliminary results show that there was a high degree of variability amongst major constituents even within the same clast type at individual sample sites. The variability in deviation found in high strain granitoid clast range between 0.02%-4.81%, low strain granitiod clast range between 0.07%-6.06%, high strain mafic clast range between 0.09%-4.78%, low strain mafic clast range between 0.01%-3.23%, high strain felsic clast range between 0.05%-5.22%, low strain felsic clast range between 0.05%-6.76%. The variability between deviations show the averages overlap showing no apparent bulk volume change between high strain and low strain regions in the Rainy Lake Region. The inherent heterogeneity in metaconglomerates allows them to be extremely useful for strain analysis purposes, but complicates geochemical characterization because original clast composition significantly varies. Therefore, we will require a large sample size to capture the variability within the population of clasts and determine the extent of fluid-assisted alteration in deformation.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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".