Water recovery rate and isotopic signature of cryogenic vacuum extracted spiked soil water following oven‐drying at different temperatures
Bibliographic record
Abstract
Abstract Extracting water from soils is often a critical step for obtaining soil water isotope information. Cryogenic vacuum extraction (CVE), the most widely used laboratory‐based removal technique, produces biased isotope composition and the mechanisms causing the biases remain uncertain. Here, we conducted spiking tests on soil samples oven‐dried at 105 and 205°C, respectively. The recovery rate and isotopic composition of the extracted water were analysed. Our results show that conventional oven‐drying (105°C) was not sufficient to liberate tightly bound water from soils but oven‐drying at temperatures above 205°C was. Part of the tightly bound water in soil was extracted by CVE, because the extraction capacity of CVE (heating at 95°C) was equivalent to oven‐drying at temperature between 105 and 205°C. Moreover, the two pretreatments yielded markedly differences in water recovery rates. And with increasing ratios of clay contents to water contents, the recovery rates of the pretreated soil at 105°C trended upward above 100%, but that of 205°C trended downward below 100%. Further, the 2H and 18O signatures of the extracted water from the soil pretreated at 205°C were both depleted relative to reference water, but the pretreatment at 105°C showed enriched 18O and depleted 2H. This suggests that oxygen isotope exchange may have occurred between tightly bound water and soil minerals, resulting in enriched 18O in water for the 105°C pretreatments. For the 205°C pretreatment, pre‐existing soil water was completely removed and relative to spiking water, isotopic signatures of the extracted water followed equilibrium fractionation law due to incomplete extraction. Therefore, our results suggested that the biased isotopic signatures of water extracted by CVE may be partially due to incomplete extraction and mixture of added water with the residual tightly bound water that pre‐exists before spiking.
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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 | 0.000 | 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".