A New Method for Determining Fluid Compositions in the H<sub>2</sub>O‐NaCl‐CaCl<sub>2</sub> System with Cryogenic Raman Spectroscopy
Bibliographic record
Abstract
Abstract Raman peaks of various hydrates in the H2O‐NaCl‐CaCl2 system have been previously identified, but a quantitative relationship between the Raman peaks and XNaCl (i.e., NaCl/(NaCl+CaCl2)) has not been established, mainly due to the difficulty to freeze the solutions. This problem was solved by adding alumina powder to the solutions to facilitate nucleation of crystals. Cryogenic (−185°C) Raman spectroscopic studies of alumina‐spiced solutions indicate that XNaCl is linearly correlated with the total peak area fraction of hydrohalite. Capsules of solutions made from silica capillary were prepared to simulate fluid inclusions. Most of these artificial fluid inclusions could not be totally frozen even at temperatures as low as −185°C, and the total peak area fraction of hydrohalite is not correlated linearly with XNaCl. However, the degree of deviation (ΔXNacl) from the linear correlation established earlier is related to the amount of residual solution, which is reflected by the ratio (r) of the baseline “bump” area, resulting from the interstitial unfrozen brine near 3435 cm−1, and the total hydrate peak area between 3350 and 3600 cm−1. A linear correlation between ΔXNaCl and r is established to estimate XNaCl from cryogenic Raman spectroscopic analysis for fluid inclusions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".