Understanding fluid behavior through ion and isotope data from the Yitong Basin, Northeast China
Bibliographic record
Abstract
To evaluate ion origins and fluid behavior, the chemical properties of thermal water sampled from the Eocene reservoir in the Yitong Basin (YB), Northeast China, were investigated. The thermal water samples are classified as Na–HCO3-type water and were fully equilibrated, except for Sijixiangkang (SJXK) and Yitong (YT). The cations originate mainly from water–rock interactions (e.g., albitization and weathering of plagioclase), while the anions originate from magmatic volatiles and leaching of limestone and granite, which were heated by hot magmatic volatiles and exhibited an evaporation-like pattern in the Gibbs diagrams. The existence of magmatic volatiles was verified by the high ion ratio, the minor-element origins, δ13C values of HCO3, and δ34S values of SO4, which flowed upward along lithospheric faults, with higher fluxes in the northeast than in the southwest (the δ13C value of the Chaluhe depression (CD) is 0.93‰ lower than that of the Moliqing depression (MD, 1.63‰)). Furthermore, according to the Br/Cl and HCO3−/Cl ratios and the δ13C values, we speculate that a deep Permian limestone reservoir exists below the granitic unit. Based on the ion origins and fluid potentials, we conclude that the CD and MD are open systems rather than closed systems. The recharged water migrates from the margin to the center in the plane, and in the vertical direction, it migrates from the Yongji (E2y) and Sheling (E2sh) strata to the overlying strata and underlying Shuangyang (E2s) strata along faults. By summarizing all of the available data, we proposed a conceptual model of fluid migration.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".