Oil contamination of sediments by freeze-drying versus air-drying for organic geochemical analysis
Bibliographic record
Abstract
Abstract Freeze-drying is widely used in geochemical laboratories for preparing wet solid environmental samples such as sediments and soils before being analyzed for their contents and states of various metal elements and labile organic components that may be temperature- and/or redox-sensitive. Screening bulk geochemical analysis of two Artic lake sediment samples prepared by freeze-drying displayed unexpectedly high contents of labile organic matter (OM) represented by the Rock–Eval S1 peaks (e.g., 8.12 and 4.84 mg HC/g sediment). The amount of labile OM was reduced greatly for the freeze-dried sediment samples after a thorough cleaning of the freeze-drier sample chamber (e.g., 2.75 and 1.46 mg HC/g sediment), but was still significantly higher than that of the equivalent air-dried samples (e.g., 0.76 and 0.23 mg HC/g sediment). Compositional analysis of the labile OM fractions by gas chromatography (GC) of both freeze-dried and air-dried aliquots of the same sediments indicates the presence of unresolved complex mixture (UCM) humps of C10–C23 hydrocarbons in the freeze-dried samples. In contrast, air-dried samples, either real sediments or blank laboratory materials represented by clean sand and thermally spent shale, do not show the C10–C23 hydrocarbon UCM humps on their GC traces. The hydrocarbon UCM humps persist in the freeze-dried samples even they further went through air-drying at ambient conditions. Both bulk and compositional analytical results in this work appear to indicate the potential risk of introduction of external hydrocarbons to the prepared materials during freeze-drying process, especially if an aged freeze-drier was used without being thoroughly cleaned and if pump oil and cooling fluids were components of the device.
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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 | 0.000 |
| 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".