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Record W2103575694 · doi:10.2144/000113362

Direct PCR amplification and sequencing of specimens’ DNA from preservative ethanol

2010· article· en· W2103575694 on OpenAlexafffund
Shadi Shokralla, Gregory A. C. Singer, Mehrdad Hajibabaei

Bibliographic record

VenueBioTechniques · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversity of Guelph
FundersOntario Genomics InstituteGenome Canada
KeywordsPreservativePolymerase chain reactionMultiple displacement amplificationDNAApplications of PCRDNA sequencingBiologyGene duplicationPrimer (cosmetics)Molecular biologyDigital polymerase chain reactionDNA extractionChemistryGeneticsGeneFood science

Abstract

fetched live from OpenAlex

DNA extraction is the first step in many molecular biology protocols. However, we hypothesized that DNA from a preserved specimen can leak into its preservative medium, allowing the medium itself to be directly PCR-amplified. We successfully tested this idea on mescal-the alcoholic beverage famous for the "worm" (a caterpillar) that is placed in the bottle of many brands-and indeed obtained amplifiable quantities of caterpillar DNA. We then successfully amplified and sequenced DNA from the 95% ethanol preservative of 70 freshly collected specimens and 7 archival specimens 7-10 years old. These results suggest that DNA extraction is a superfluous step in many protocols and that preservative ethanol can be used as a source of genetic material for non-invasive sampling or when no tissue specimen is left for further DNA analyses.

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)0.003
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.024
GPT teacher head0.230
Teacher spread0.206 · 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

Citations103
Published2010
Admission routes2
Has abstractyes

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