Bibliographic record
Abstract
Endogenous toxins'' could be defined as toxins formed within the body, which can result in disease.However, as Prestwick and Dedon (Chapter 1) note, there is a ''blur'' between ''endogenous'' and ''exogenous'' toxins and where the toxin is formed.There is also a ''blur'' with relation to the body and where it begins.Can lipopolysaccharide (LPS) endotoxins formed by common colonic bacteria be considered endogenous toxins?Are compounds formed endogenously in plants that are toxic to the animal consuming them, for example, solanine, psoralins, and the cyanogenic glycosides, ''endogenous toxins''?And there is the ''blur'' of disease.The demonstration of a clear association between suspected toxins resulting from diet and a disease state is not an easy exercise.The problem may be somewhat easier with toxins resulting from metabolic diseases, but even then, demonstration of causation can often be established only with successful intervention.Perhaps, it is easiest to consider the array of endogenous toxins considered in this book and ask what other term might be more useful?This is clearly a huge area of toxicology and a likely cause of many human diseases.The formation and toxicity of ''endogenous toxins,'' with their association with diet, lifestyle, and genetic inborn errors of metabolism on the one hand, and disease on the other, is complex.We can all benefit from the help of others to clarify the role of endogenous toxins however we define them.2 Why consider ''alcohol drinking'' in a review of endogenous toxins?Methanol and formaldehyde, formed in vivo as a by-product of their methylation function [1-3], can certainly be considered endogenous toxins, but ethanol would seem to be an exogenous toxin, not an endogenous one.We have considered ethanol in this discussion both because the endogenous toxins formed in the body with the consumption of ethyl alcohol describes the complexity of the relationship between Endogenous Toxins.Diet, Genetics, Disease and Treatment.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.717 | 0.475 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".