Contamination risk of stable isotope samples during milling
Bibliographic record
Abstract
RATIONALE: Isotope analysis of wood is an important tool in dendrochronology and ecophysiology. Prior to mass spectrometry analysis, wood must be homogenized, and a convenient method involves a ball mill capable of milling samples directly in sample tubes. However, sample-tube plastic can contaminate wood during milling, which could lead to biological misinterpretations. METHODS: We tested possible contamination of whole wood and cellulose samples during ball-mill homogenization for carbon and oxygen isotope measurements. We used a multi-factorial design with two/three steel milling balls, two sample amounts (10 mg, 40 mg), and two milling times (5 min, 10 min). We further analyzed abrasion by milling empty tubes, and measured the isotope ratios of pure contaminants. RESULTS: A strong risk exists for carbon isotope bias through plastic contamination: the δ(13) C value of polypropylene deviated from the control by -6.77‰. Small fibers from PTFE filter bags used during cellulose extraction also present a risk as the δ(13) C value of this plastic deviated by -5.02‰. Low sample amounts (10 mg) showed highest contamination due to increased abrasion during milling (-1.34‰), which is further concentrated by cellulose extraction (-3.38‰). Oxygen isotope measurements were unaffected. CONCLUSIONS: A ball mill can be used to homogenize samples within test tubes prior to oxygen isotope analysis, but not prior to carbon or radiocarbon isotope analysis. There is still a need for a fast, simple and contamination-free sample preparation procedure. Copyright © 2016 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".