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Record W2785613280 · doi:10.1139/cjm-2017-0278

Microbial diversity and community structure in agricultural soils suffering from 4 years of Pb contamination

2018· article· en· W2785613280 on OpenAlexvenueno aff
Fengqiu An, Diao Zhan, Jialong Lv

Bibliographic record

VenueCanadian Journal of Microbiology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicChromium effects and bioremediation
Canadian institutionsnot available
FundersMinistry of Agriculture of the People's Republic of China
KeywordsGemmatimonadetesRelative species abundanceMicrobial population biologyBiologyArthrobacterOrganic matterEnvironmental chemistrySoil waterFirmicutesProteobacteriaAbundance (ecology)EcologyEdaphicRamsar siteBacteriaBotany16S ribosomal RNAChemistry

Abstract

fetched live from OpenAlex

Heavy metal pollution has become a widespread environmental problem due to rapid economic development. The phylogenetic diversity and structure of microbial communities in lead (Pb)-contaminated Lou soils were investigated using Illumina MiSeq sequencing of 16S rRNA genes. The presence of Pb 2+ in soil showed weak impact on the diversity of soil bacteria community, but it influenced the abundance of some genera of bacteria, as well as soil physicochemical properties. We found significant differences in the relative abundances of heavy-metal-resistant bacteria such as Bacillus, Streptococcus, and Arthrobacter at the genus level. Available Pb and total Pb negatively correlated with soil organic matter but positively affected available phosphorus. The abundance of main bacteria phyla was highly correlated with total Pb. The relative abundance of Gemmatimonadetes, Nitrospirae, and Planctomycetes was negatively correlated with total Pb. Collectively, Pb influences both the microbial community composition and physicochemical properties of soil.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

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

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 head0.173
Teacher spread0.167 · 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 designObservational
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

Citations17
Published2018
Admission routes1
Has abstractyes

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