An Aryl Hydrocarbon Receptor Odyssey to the Shores of Toxicology: The Deichmann Lecture, International Congress of Toxicology-XI
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
The science of toxicology is devoted, in large part, to understanding mechanisms of toxicity so that we can more accurately assess the risk posed by exposure to xenobiotic agents and, perhaps, intervene in the toxicologic process to mitigate harm. Dioxin-like chemicals continue to be of great concern as environmental toxicants. About 30 years ago the aryl hydrocarbon receptor (AHR) was discovered as a specific binding site for 2,3,7,8-tetrachlorodibenzo-p-dioxin. This giant step led to our current view that essentially all toxic effects of dioxins are AHR-mediated. The AHR serves as the archetype for understanding toxicity mediated by other soluble receptors. The fact that toxicity is receptor-mediated has important implications, especially for dose-response relationships. In laboratory animals genetic differences in AHR gene structure lead to profound differences in responsiveness to dioxin-like chemicals. Humans, however, exhibit relatively few AHR polymorphisms and these seem to exert only modest effects on downstream events. Dioxin toxicity is fundamentally due to AHR-mediated dysregulation of gene expression. Our current challenging goal is to determine which dysregulated genes underlie specific forms of dioxin toxicity. Mapping AHR-mediated gene expression in a variety of biological systems may help explain why dramatic differences in susceptibility to dioxin toxicity exist among laboratory species and why humans appear to be relatively resistant to adverse effects of dioxins.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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