Palaeoparasitology and palaeogenetics: review and perspectives for the study of ancient human parasites
Bibliographic record
Abstract
While some species of parasites can be identified to species level from archaeological remains using microscopy (i.e. Enterobius vermicularis, Clonorchis sinensis), others can only be identified to family or genus level as different species produce eggs with similar morphology (i.e. Tænia sp. and Echinococcus sp.). Molecular and immunological approaches offer the possibility to provide more precise determination at the species level. They can also identify taxa when classic parasite markers such as eggs or cysts have been destroyed over time. However, biomolecules can be poorly preserved and modern reference DNA is available only for a limited number of species of parasites, leading to the conclusion that classic microscopic observation should be combined with molecular analyses. Here we present a review of the molecular approaches used over the past two decades to identify human pathogenic helminths (Ascaris sp., Trichuris sp., E. vermicularis, Fasciola sp. etc.) or protists (Giardia sp., Trypanosoma sp., Leishmania sp. etc.). We also discuss the prospects for studying the evolution of parasites with genetics and genomics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".