Integrated DNA and Fingerprint Analyses in the Identification of 60‐Year‐Old Mummified Human Remains Discovered in an Alaskan Glacier
Bibliographic record
Abstract
This report describes the identification of a merchant mariner who perished in 1948 when Northwest Airlines Flight 4422, a DC-4 carrying 24 seamen and six crew members crashed into Mount Sanford, Alaska. Fifty-one years later, a human forearm and hand were found close by the wreckage of the plane, prompting identification efforts using DNA and fingerprints. There were significant challenges to both the fingerprint and DNA analyses. The hand was badly desiccated, making fingerprint friction-ridge detail almost invisible and the remains had been embalmed upon discovery, making DNA amplification difficult. We present the results of an interdisciplinary approach that successfully addressed these challenges and ultimately led to the identification of the remains. These efforts relied on efficient fingerprint rejuvenation and imaging techniques that improved print resolution, as well as new DNA extraction techniques optimized for aggressively embalmed remains.
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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 | 0.002 | 0.001 |
| 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".