Interpreting the Effects of Burning on Pre‐incineration Saw Marks in Bone
Bibliographic record
Abstract
This study examined the effects of fire on the features associated with saw marks in bone. Both class and individual characteristics were examined using stereomicroscopy and scanning electron microscopy (SEM). Twenty-four semifleshed Sus scrofa L. tibiae were sawed into three sections with the middle section having deep and shallow false starts. Twelve saw blades of varying age and type were each used to cut two tibiae. In each case, the first tibia was burned in an outdoor open fire to the point of partial calcination. The second tibia, our control, was macerated using a heated enzyme solution. Controls and burned specimens were examined for the following characteristics: breakaway spur, tooth hop, false start, exit chipping, tooth imprint, breakaway notch, pull out striae, kerf flare, and blade drift. In general, there was parity in the observed characteristics in the burned samples using the SEM and the stereomicroscope. SEM observation, however, provided enhanced images, with the addition of observing individual tooth imprints, previously not visible. Therefore, this study recommends using an SEM for the examination of saw cuts in burnt bone.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".