Chemical and isotopic characterisation of highly saline sedimentary pore water
Bibliographic record
Abstract
Pore water chemistry and isotopic composition were investigated using common indirect methods (leaching and isotope diffusive-exchange technique) on drillcore samples from the DGR boreholes drilled by Ontario Power Generation (OPG) at Bruce, southern Ontario, into Palaeozoic rock of the Michigan Basin. Previously, these methods were successfully applied to characterise pore waters of the Opalinus Clay drillcore samples from Mont Terri, Switzerland, which showed a maximum Cl- content of approx. 14 g/kgH2O. In contrast to the Opalinus Clay, however, the Michigan Basin samples are characterised by highly saline pore water, which induces several methodological difficulties. The conversion of aqueous leaching data to mass of pore water requires the knowledge of rock's porosity and thus its water content, grain and bulk densities. The measurements of densities and water content are, however, affected by the mass and volume of evaporated pore-water salts and the dry weight of the rock sample requires a correction related to the pore water salinity. Applying the common salinity-correction method in combination with the general trend in the depth profile given by the water activity data of the rock samples allows an evaluation of the chloride content and main salt components (NaCl vs. CaCl2) of the pore water over a range of salinities from seawater to halite saturation. The high salinity also affects the indirect methods for the pore-water stable isotope determination. In the isotope diffusive-exchange technique, where the isotope exchange between a test water and pore water of rock samples occurs via the vapour phase, there exists a risk of liquid-vapour isotope fractionation of oxygen and hydrogen between the test water and the highly saline pore water. Differences in the water activity will result in saturation/desaturation processes and possible precipitation of (hygroscopic) salts in the rock sample over the course of the experiment. We propose to minimise this fractionation by fitting the water activities of the test-water solution to that in the investigated rock sample by adding NaCl or CaCl2 to the test water. Similar perturbations of the in situ isotope signature during the experiment and measurements will also have to be expected for other porewater stable isotope
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".