Multimethod Resolution of a Small‐Scale Case of Commingling
Bibliographic record
Abstract
This study highlights the use of multiple methods for resolving a case of commingled human remains. Skeletal remains were located in a marijuana field in rural northern California by law enforcement. Although initially buried in shallow graves, the remains of two decedents were disturbed by large carnivores and scattered over a wide area. The remains were submitted by law enforcement for forensic anthropological analysis and resolution of commingling. To segregate the remains of the two individuals, a number of methods were employed, including: (i) physical matching of fragmented remains; (ii) articulation to evaluate joint congruence; (iii) visual pair-matching of bilateral elements; (iv) osteometric pair-matching; (v) evaluation of taphonomic patterns; (vi) DNA analysis; and (vii) portable X-ray spectrometry (pXRF). This multimethod approach resulted in accurate resolution of the commingling and facilitated reconstruction of the biological profiles, taphonomic patterns, and trauma analysis for each individual.
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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 | 0.000 | 0.029 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".