When big data initiatives meet: Data sharing between THANADOS and IsoArcH for early medieval cemeteries in Austria
Bibliographic record
Abstract
This paper reports carbon, nitrogen, and sulfur stable isotope data obtained from bone collagen of humans from the early medieval cemeteries of Hemmaberg/Gora svete Heme and Oberleiserberg located in Austria. The Hemmaberg/Gora svete Heme cemetery, dating from the 8th to the 11th century, comprises 29 graves, from which 15 individuals were analyzed. The Oberleiserberg cemetery, established in the first half of the 11th century, includes 71 graves as well as several incidental finds of human bones, from which 75 samples were analyzed. Both cemeteries show comparable δ13C data (mean for Oberleiserberg: –17.5 ± 1.2 ‰, 1σ; mean for Hemmaberg: –16.4 ± 1.6‰, 1σ). However, the δ15N values of individuals from Oberleiserberg (mean: +10.4 ± 1.5‰, 1σ) are slightly higher than those of individuals from Hemmaberg/Gora svete Heme (mean: +8.8 ± 1.1‰,1σ). The δ34S values were only obtained on the individuals from Oberleiserberg, and show a mean value of –0.9 ± 2.0 ‰ (1σ). Beyond the isotopic data presented in this article, we lay the foundations for cooperation between the IsoArcH database (https://isoarch.eu) [1] and the THANADOS (https://thanados.net) [2] project. While IsoArcH primarily stores isotope-related datasets for bioarchaeology, THANADOS stores data on archaeologically and anthropologically researched burials. Moving forward, IsoArcH and THANADOS plan to work closely together to integrate their databases. This collaboration presents a promising opportunity for both projects to pool their resources and knowledge, offering a wealth of information for researchers and the general public who are interested in anthropology and archaeology.
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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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".