Comparing laboratory- and field-measured biota–sediment accumulation factors
Bibliographic record
Abstract
Standardized laboratory protocols for measuring the accumulation of chemicals from sediments are used in assessing new and existing chemicals, evaluating navigational dredging materials, and establishing site-specific biota-sediment accumulation factors (BSAFs) for contaminated sediment sites. The BSAFs resulting from the testing protocols provide insight into the behavior and risks associated with individual chemicals. In addition to laboratory measurement, BSAFs can also be calculated from field data, including samples from studies using in situ exposure chambers and caging studies. The objective of this report is to compare and evaluate paired laboratory and field measurement of BSAFs and to evaluate the extent of their agreement. The peer-reviewed literature was searched for studies that conducted laboratory and field measurements of chemical bioaccumulation using the same or taxonomically related organisms. In addition, numerous Superfund and contaminated sediment site study reports were examined for relevant data. A limited number of studies were identified with paired laboratory and field measurements of BSAFs. BSAF comparisons were made between field-collected oligochaetes and the laboratory test organism Lumbriculus variegatus and field-collected bivalves and the laboratory test organisms Macoma nasuta and Corbicula fluminea. Our analysis suggests that laboratory BSAFs for the oligochaete L. variegatus are typically within a factor of 2 of the BSAFs for field-collected oligochaetes. Bivalve study results also suggest that laboratory BSAFs can provide reasonable estimates of field BSAF values if certain precautions are taken, such as ensuring that steady-state values are compared and that extrapolation among bivalve species is conducted with caution.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".