Technical note: Examining the use of ethylenediaminetetraacetic acid for humic extraction of ancient bone
Bibliographic record
Abstract
Abstract We examined the efficacy of ethylenediaminetetraacetic acid (EDTA) for removing humic contaminants from collagen extracted from ancient bone. Humic contaminants must be removed to obtain reliable stable isotope values from ancient bone collagen, given that humic acids have consistently lower δ13C values than collagen. The purpose of our research was to examine if EDTA treatment could effectively remove humic contaminants from bone collagen and thus serve as an alternative to the commonly implemented sodium hydroxide (NaOH) treatment, which may be associated with large collagen losses in poorly preserved samples. We compared the isotopic and elemental composition of ancient samples treated with EDTA alone, samples demineralized in hydrochloric acid (HCl) and rinsed in EDTA, samples treated with HCl alone, and samples demineralized in HCl and rinsed with NaOH. The samples used in the analyses were selected because they presented evidence of substantial humic contamination. We found that NaOH was the most effective agent for reducing humic contaminants as evidenced by the samples treated with this agent having higher δ13C values and lower C:N ratios relative to other treatments. The results from samples treated with EDTA suggest that this chemical cannot effectively remove humic contaminants given that these samples had significantly higher C:N ratios and lower δ13C and δ15N values relative to the HCl/NaOH treatment. Our results demonstrate that when performing stable isotope analysis of ancient bone collagen suspected to be contaminated with humic acids, NaOH is the most effective chemical agent to remove humic contaminants, while EDTA cannot perform this task.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".