The Representation and Weathering of Human Remains
Bibliographic record
Abstract
Disarticulated, commingled, and fragmented assemblages occur over a range of geographic and temporal contexts, yet the relationship between the representation and weathering of bone in these collections is unclear. Previous studies have produced inconsistent results and there is little elaboration discussing why the representation of large bones differ from small bones in archaeological collections containing commingled remains. The purpose of this research was to determine which bones were better represented, and if the representation correlated to the weathering of bone in the collection of human remains from the Battle of Stoney Creek, a War of 1812 site. The soldiers from the battle were likely buried in a mass grave; however, almost 200 years of extensive taphonomic disturbances created an assemblage that was disarticulated, commingled, and fragmented. A database of the collection was used to gather information on bone fragment completeness recorded using the zonation method (Knüsel and Outram 2004), and weathering scores recorded using the scale by McKinley (2004). Results from the Z-statistic and Wilcoxon Rank-Sum statistic indicated that small bones (metacarpals, metatarsals, tali and calcanei) were better represented and less weathered than long upper and lower limb bones (femora, tibiae, fibulae, humeri, ulnae and radii) (p=0.05). The binomial distribution also determined that the crania were underrepresented in comparison to two cemetery sites; the West Tenter Street and Cross Bones burial ground (p=0.1). There are a number of possible reasons for this expression of representation and weathering including the size, morphology, and density of bones, taphonomic disturbances, the burial environment (e.g., soil characteristics, the feather edge effect), and clothing. This study highlights the importance of preservation analyses in commingled, disarticulated, and fragmented collections. The findings from this research suggest that small bones may be better represented than the larger limb bones at sites with extensive taphonomic disturbances.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".