Guidance for evaluating in vivo fish bioaccumulation data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, the laboratory-derived fish bioconcentration factor (BCF) serves as one of the primary data sources used to assess the potential for a chemical to bioaccumulate. Consequently, fish BCF values serve a central role in decision making and provide the basis for development of quantitative structure-property relationships (QSPRs) used to predict the bioaccumulation potential of untested compounds. However, practical guidance for critically reviewing experimental BCF studies is limited. This lack of transparent guidance hinders improvement in predictive models and can lead to uninformed chemical management decisions. To address this concern, a multiple-stakeholder workshop of experts from government, industry, and academia was convened by the International Life Sciences Institute Health and Environmental Sciences Institute to examine the data availability and quality issues associated with in vivo fish bioconcentration and bioaccumulation data. This paper provides guidance for evaluating key aspects of study design and conduct that must be considered when judging the reliability and adequacy of reported laboratory bioaccumulation data. Key criteria identified for judging study reliability include 1) clear specification of test substance and fish species investigated, 2) analysis of test substance in both fish tissue and exposure medium, 3) no significant adverse effects on exposed test fish, and 4) a reported test BCF that reflects steady-state conditions with unambiguous units. This guidance is then applied to 2 data-rich chemicals (anthracene and 2,3,7,8-tetrachlorodibenzo-p-dioxin) to illustrate the critical need for applying a systematic data quality assessment process. Use of these guidelines will foster development of more accurate QSPR models, improve the performance and reporting of future laboratory studies, and strengthen the technical basis for bioaccumulation assessment in chemicals management.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it