Evaluation of Isotopic Enrichment Factors for the Biodegradation of Chlorinated Ethenes Using a Parameter Estimation Model: Toward an Improved Quantification of Biodegradation
Bibliographic record
Abstract
A model was developed to predict the concentrations of chlorinated ethenes and ethene during sequential reductive dechlorination of tetrachloroethene (PCE) from stable carbon isotope values using Rayleigh model principles and specified isotopic enrichment factors for each step of dechlorination. The model was tested using three separate datasets of concentration and isotope values measured during three experiments involving the degradation of PCE to vinyl chloride (VC), trichloroethene (TCE) to ethene, and cis-1,2-dichloroethene (cDCE) to ethene. The model was then coupled to a parameter estimation method to estimate values for the isotopic enrichment factors of TCE, cDCE, and VC when they are intermediates in the dechlorination to ethene. The enrichment factors estimated for TCE and cDCE when they were intermediates in biodegradation experiments were close to or within the published range of enrichment factors determined from experiments where TCE or cDCE were the initial substrates. In contrast, the enrichment factors determined by parameter estimation for experiments in which VC was an intermediate in biodegradation experiments were consistently more negative (by approximately 10 per thousandth) than the most negative published enrichment factor determined from experiments where VC was the initial substrate. This finding suggests that the range of enrichment factors for VC dechlorination may not be as narrow as previously suggested (-21.5 per thousandth to -26.6 per thousandth) and that fractionation during VC dechlorination when VC is an intermediate compound may be significantly larger than when VC is the initial substrate. These findings have important implications both for the current practice of extrapolating laboratory-derived isotopic enrichment factors to quantify biodegradation of chlorinated ethenes in the field and for understanding the details of enzymatic reductive dechlorination.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".