MétaCan
Menu
Back to cohort

Biotransformation of RDX and HMX by Anaerobic Granular Sludge with Enriched Sulfate and Nitrate

2017· article· en· W2748053368 on OpenAlexafffund
Chunjiang An, Yarong Shi, Yanling He, Guohe Huang, Yonghong Liu, Shu-Cheng Yang

Bibliographic record

VenueWater Environment Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNitrateBiotransformationSulfateChemistryEnvironmental chemistryBioreactorBiodegradationTrinitrotolueneExplosive material

Abstract

fetched live from OpenAlex

RDX and HMX are widely used energetic materials and they are recognized as environmental contaminants at numerous locations. The present study investigated the biotransformation of RDX and HMX by anaerobic granular sludge under sulfate- and nitrate-enriched conditions. The results showed that RDX and HMX could be transformed by anaerobic granular sludge when nitrate was present. However, the biotransformation of RDX and HMX was negatively influenced, especially with high nitrate concentrations. Sulfate-enriched conditions were more favorable for the removal of ammunition compounds by anaerobic granular sludge than nitrate-enriched conditions. The removal of RDX and HMX under both nitrate- and sulfate-enriched conditions was facilitated by the use of glucose as additional substrate. This knowledge may help identify factors required for rapid removal of RDX and HMX in high-rate bioreactors. These results can also be applied to devise an appropriate and practical biological treatment strategy for explosive contaminated wastewater.

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 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 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 score0.173
Threshold uncertainty score0.779

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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 teacher head, 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

Citations9
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueWater Environment ResearchSame topicMicrobial bioremediation and biosurfactantsFrench-language works237,207