Palaeoparasitology and palaeogenetics: review and perspectives for the study of ancient human parasites
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
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.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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