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DNA Preservation in Skeletal Elements from the World Trade Center Disaster: Recommendations for Mass Fatality Management*<sup>,†</sup>

2009· article· en· W2141097600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Forensic Sciences · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsWorld trade centerPoison controlCase fatality rateForensic engineeringMedicineToxicologyBiologyEnvironmental healthEngineeringGeographyArchaeologyPopulation

Abstract

fetched live from OpenAlex

The World Trade Center (WTC) victim identification effort highlights taphonomic influences on the degradation of DNA from victims of mass fatality incidents. This study uses a subset of the WTC-Human Remains Database to evaluate differential preservation of DNA by skeletal element. Recovery location, sex, and victim type (civilian, firefighter, or plane passenger) do not appear to influence DNA preservation. Results indicate that more intact elements, as well as elements encased in soft tissue, produced slightly higher identification rates than more fragmented remains. DNA identification rates by element type conform to previous findings, with higher rates generally found in denser, weight-bearing bones. However, smaller bones including patellae, metatarsals, and foot phalanges yielded rates comparable to both femora and tibiae. These elements can be easily sampled with a disposable scalpel, and thus reduce potential DNA contamination. These findings have implications for DNA sampling guidelines in future mass fatality incidents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.318
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it