Success Rates of Recovering Teeth and Infant-Sized Bones Dispersed among Leaf Litter
Bibliographic record
Abstract
Previous research (Pokines et al. 2018) examined the success rates of search through leaf litter for older juvenile- to adult-sized bones in a New England forest environment. Individual element size class had a significant effect upon recovery rate. Using the same experimental conditions, the present research examined the recovery rates for infant-sized bones and adult-sized teeth. Ten simulated outdoor scenes were sown with dispersed, skeletonized, infant-sized pig (Sus scrofa) bones of different types and pig teeth comparable in size to adult human. Processing was executed through a hand-and-knee crawl while picking through and collecting all leaf litter by hand and then emptying it onto a tarp, where the effects of searching the same leaf litter twice were examined. Recovery rates from primary search ranged from 62.4% to 74.7% per trial with an overall rate of 68.8%, which was significantly lower than the overall recovery rate of 76.7% for the previous research. Secondary search recovered an additional 17.9% of bone, leading to an overall recovery rate of 86.7%. Teeth were recovered through primary search at an overall rate of 38.0%, with an additional 12.0% recovered through secondary search. Significant differences in recovery rate for the infant-sized remains based upon bone size were noted. Forensic archaeologists are cautioned that full recovery cannot be assumed in these situations. Careful primary searching by hand combined with secondary searching may mitigate the loss of evidence in some situations and should be considered for forensic search protocols, especially where infant skeletal remains are suspected to be present.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.056 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".