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Record W2982598041 · doi:10.1128/msphere.00334-19

Validating DNA Extraction Protocols for Bentonite Clay

2019· article· en· W2982598041 on OpenAlexafffund
Katja Engel, Sara Coyotzi, Melody A. Vachon, Jennifer McKelvie, Josh D. Neufeld

Bibliographic record

VenuemSphere · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsNuclear Waste Management OrganizationUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaNuclear Waste Management Organization
KeywordsBentoniteExtraction (chemistry)GeologyEnvironmental scienceGeotechnical engineeringChemistryChromatography

Abstract

fetched live from OpenAlex

Extraction of microbial DNA from MX-80 bentonite is challenging due to low biomass and adsorption of nucleic acid molecules to the charged clay matrix. Blocking agents improve DNA recovery, but their impact on microbial community profiles from low-biomass samples has not been characterized well. In this study, we evaluated the effect of casein and phosphate as blocking agents for quantitative recovery of nucleic acids from MX-80 bentonite. Our data justify a simplified framework for analyzing microbial community DNA associated with swelling MX-80 bentonite samples within the context of a deep geological repository for used nuclear fuel. This study is among the first to demonstrate successful extraction of DNA from Wyoming MX-80 bentonite.

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)0.006
metaresearch head score (Gemma)0.008
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
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)0.0020.002

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 head0.014
GPT teacher head0.336
Teacher spread0.321 · 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
GenreMethods

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

Citations27
Published2019
Admission routes2
Has abstractyes

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