An extensive archaeological dental calculus dataset spanning 5000 years for ancient human oral microbiome research
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
Archaeological dental calculus can provide detailed insights into the ancient human oral microbiome. We offer a multi-period, multi-site, ancient shotgun metagenomic dataset consisting of 174 samples obtained primarily from archaeological dental calculus derived from various skeletal collections in the United Kingdom. This article describes all the materials used including the skeletons' historical period and burial location, biological sex, and age determination, data accessibility, and additional details associated with environmental and laboratory controls. In addition, this article describes the laboratory and bioinformatic methods associated with the dataset development and discusses the technical validity of the data following quality assessments, damage evaluations, and decontamination procedures. Our approach to collecting, making accessible, and evaluating bioarchaeological metadata in advance of metagenomic analysis aims to further enable the exploration of archaeological science topics such as diet, disease, and antimicrobial resistance (AMR).
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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