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Record W2025203431 · doi:10.1111/1556-4029.12561

Elimination of Bioweapons Agents from Forensic Samples During Extraction of Human DNA

2014· article· en· W2025203431 on OpenAlexafffundabout
Jason Timbers, D. Adrian Wilkinson, Christine C. Hause, Myron L. Smith, Mohsin Abbas Zaidi, Denis Laframboise, Kathryn E. Wright

Bibliographic record

VenueJournal of Forensic Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsCarleton UniversityPublic Health Agency of CanadaUniversity of OttawaOttawa Public HealthRoyal Canadian Mounted Police
FundersRoyal Canadian Mounted Police
KeywordsDNA extractionEndosporeDNA profilingBiologyDNABacteriaMicrobiologyIsolation (microbiology)SporePolymerase chain reactionGeneticsGene

Abstract

fetched live from OpenAlex

Collection of DNA for genetic profiling is a powerful means for the identification of individuals responsible for crimes and terrorist acts. Biologic hazards, such as bacteria, endospores, toxins, and viruses, could contaminate sites of terrorist activities and thus could be present in samples collected for profiling. The fate of these hazards during DNA isolation has not been thoroughly examined. Our goals were to determine whether the DNA extraction process used by the Royal Canadian Mounted Police eliminates or neutralizes these agents and if not, to establish methods that render samples safe without compromising the human DNA. Our results show that bacteria, viruses, and toxins were reduced to undetectable levels during DNA extraction, but endospores remained viable. Filtration of samples after DNA isolation eliminated viable spores from the samples but left DNA intact. We also demonstrated that contamination of samples with some bacteria, endospores, and toxins for longer than 1 h compromised the ability to complete genetic profiling.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.323
Teacher spread0.286 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2014
Admission routes3
Has abstractyes

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