Intestinal absorption and biomagnification of organic contaminants in fish, wildlife, and humans
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
Methods for the regulatory assessment of the bioaccumulation potential of organic chemicals are founded on empirical measurements and mechanistic models of dietary absorption and biomagnification. This study includes a review of the current state of knowledge regarding mechanisms and models of intestinal absorption and biomagnification of organic chemicals in organisms of aquatic and terrestrial food chains and also includes a discussion of the implications of these models for assessing the bioaccumulation potential of organic chemicals. Four mechanistic models, including biomass conversion, digestion or gastrointestinal magnification, micelle-mediated diffusion, and fat-flush diffusion, are evaluated. The models contain many similarities and represent an evolution in understanding of chemical bioaccumulation processes. An important difference between the biomagnification models is whether intestinal absorption of an ingested contaminant occurs solely via passive molecular diffusion through serial resistances or via facilitated diffusion that incorporates an additional advective transport mechanism in parallel (i.e., molecular ferrying within gastrointestinal micelles). This difference has an effect on the selection of physicochemical properties that best anticipate the bioaccumulative potential of commercial chemicals in aquatic and terrestrial food chains. Current regulatory initiatives utilizing Kow threshold criteria to assess chemical bioaccumulation potential are shown to be unable to identify certain bioaccumulative substances in air-breathing animals. We urge further research on dietary absorption and biomagnification of organic chemicals to develop better models for assessing the bioaccumulative nature of organic chemicals.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it