Investigating a Medieval Church and Cemetery (Văleni-Popdomb, Harghita Country)
Bibliographic record
Abstract
"An outstanding opportunity for the investigation of the ruined medieval church emerged through the cooperation between the Haaz Rezső Museum and the Canadian company ArchaeoTek, who backed the archaeological excavation in support of academic training. As a result, anthropology students take part in the excavation, after which they analyze and interpret the discovered bones. During six seasons of work we finished the excavation of the entire church, and also we documented 661 graves. Excavation and analysis at the Papdomb site follow American bioarchaeological methods and interpretive strategies. Over the last forty years, bioarchaeology has developed into a sophisticated and collaborative enterprise that draws from a range of people and skillsets to answer social questions using biological data. Areas of expertise and analysis being applied at the Papdomb site include: skeletal excavation methods; the development of biological profiles; radiocarbon dating; diet analysis through isotope testing; and, sex and biological relationship investigation through ancient DNA. The overarching goal in using the bioarchaeological approach is to add valuable insight and complement what historians and other experts of Szekler history already know. Furthermore, work at the Papdomb site stands out for its international and multi‑scalar collaborative approach. An international team of experts works with the descendant community to preserve and study the site and the human remains. Finally, the excavation and materials produced are a valuable teaching tool for aspiring bioarchaeologists and forensic anthropologists because human remains excavation and large human skeletal collections are not common in the United States or are not available for training."
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".