Effects of sample drying on element forms in lake sediments
Bibliographic record
Abstract
The application of a sequential extraction scheme provides information on the phase association of elements in a sample, such phases being described, for example, as ‘exchangeable/adsorbed’, ‘amorphous Fe/Al oxides’ and ‘soluble organics’. It is therefore critical to maintain the chemistry of a sample from the time of collection to its analysis and during its preparation for analysis. This paper focuses on the redistribution of elements, amongst five operationally defined phases, that occurs on air-drying of the sample; the effect of subsequent storage of the sample is not addressed. Two lake sediment cores (‘Green Lake’, 31 cm, and ‘Gravel Pit Lake’, 19 cm) were sampled at 1-cm intervals and divided into two sets immediately prior to sequential leach analysis of the ‘wet’ sample. The other set was air-dried prior to sequential leach analysis. Most of the 39 elements determined in the Green Lake sediment showed, on drying, a redistribution to more labile forms. For example, increases in Fe concentration in the oxide phases were observed with a concomitant decrease in the crystalline forms of Fe reporting to the final aqua regia digestion. These changes are generally small in magnitude (<10% of the total element extracted) but they can change the shape of the element profile down the core for an affected leach which in turn could lead to misinterpretation of the sequential leach data. Surprisingly, S did not show any changes on drying, suggesting that the kinetics of oxidation are reasonably slow and that storage of the sample rather than drying is more important. The fact that some elements in the Gravel Pit Lake core behaved differently to Green Lake indicates that redistribution of elements on sample drying is both element and matrix dependent.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".