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Effect of experimental contamination with the explosive hexahydro-1,3,5-trinitro-1,3,5-triazine on soil bacterial communities

2003· article· en· W1995877607 on OpenAlexaff
David Juck, Brian T. Driscoll, Trevor C. Charles, Charles W. Greer

Bibliographic record

VenueFEMS Microbiology Ecology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsUniversity of WaterlooMcGill UniversityBiotechnology Research Institute
Fundersnot available
KeywordsBiologyTemperature gradient gel electrophoresisContaminationEnvironmental chemistryLoam16S ribosomal RNASoil contaminationMicrobiologyBacteriaSoil waterEcologyChemistryGenetics

Abstract

fetched live from OpenAlex

The effect of contamination with the explosive hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) on an indigenous soil bacterial community was examined in two uncontaminated loam soil columns possessing native grasses. One column was spiked twice with RDX crystals for a total RDX load of 1000 mg (kg soil)(-1). The reduced metabolite of RDX degradation, hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine, was observed in the column leachate, suggesting anaerobic degradation of RDX. Denaturing gradient gel electrophoresis of PCR-amplified 16S rDNA from both contaminated and uncontaminated columns produced identical banding patterns which were stable over the course of the experimental period. The bacterial diversity remained high in the contaminated column, as determined by restriction fragment length polymorphism and rarefaction analyses of random 16S rDNA clones. These combined results suggested that long-term exposure to 1000 mg RDX (kg soil)(-1) did not produce an observable effect on bacterial diversity or the numerically dominant members of the indigenous soil bacterial community.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations21
Published2003
Admission routes1
Has abstractyes

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