Experimental Formation of Marine Abrasion on Bone and the Forensic Postmortem Submergence Interval
Bibliographic record
Abstract
Human skeletal remains are frequently recovered from marine environments, where they have undergone months or years of immersion, and decomposition stage is no longer a possible method from which to estimate the postmortem submergence interval (PMSI). Over these longer PMSIs, a common taphonomic alteration that forms is the wearing and rounding of surfaces from marine abrasion, caused by repeated agitation in sediment or against rocks. Little is known about the timing of these changes and how to measure or score the degree of alteration. In a laboratory setting, multiple dry, defleshed bones of white-tailed deer (Odocoileus virginianus) were agitated in saltwater for varying intervals with abrasive sediment (1, 2, 4, 6, 8, and 10 days) and with rocks (5 and 12 days) using a laboratory tumbling device. These were compared to human remains cases from the Office of the Chief Medical Examiner, Boston, MA that had been in the Atlantic Ocean for known intervals. A five-stage (0–4) marine abrasion scoring system was devised for the taphonomic analysis of forensic cases from marine environments to allow for direct comparison among cases. A high degree of correlation between abrasion stage and known PMSI was detected.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".