Estimating Biological Characteristics With Virtual Laser Data
Bibliographic record
Abstract
Abstract Laser scanning technology is increasingly being used in forensic anthropological research to obtain virtual data for archival purposes and post hoc measurement collection. This research compared the measurement accuracy of two laser scanners—the FARO Focus 3D 330X and the FARO Freestyle 3D —against traditionally obtained (i.e., by hand) control data ( N = 454). Skeletal data were collected to address a novel question: the ability of laser scanning technology to produce measurements useful for biological characteristic estimation, such as sex and stature. Results indicate that both devices produced measurements very similar to control ( c . 3‐mm average absolute error), but also illuminate a tendency to under‐measure. Despite these findings, the virtual data produced sex and stature estimates that varied little from control‐produced estimates, signifying the usefulness of virtual data for preliminary biological identification when the skeletal elements are no longer available for physical analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.050 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".