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Record W1820439279 · doi:10.1139/w2012-016

Phylogenetic diversity of nitrogen-fixing bacteria and the<i>nifH</i>gene from mangrove rhizosphere soil

2012· article· en· W1820439279 on OpenAlexvenueno aff
Jianyin Liu, Mengjun Peng, Youguo Li

Bibliographic record

VenueCanadian Journal of Microbiology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBiologyRhizosphereMangroveGammaproteobacteriaPhylogenetic diversityBotanyPhylogenetic treeDiazotrophNitrogen fixationBacteriaEcology16S ribosomal RNAGeneticsGene

Abstract

fetched live from OpenAlex

Nine types of nitrogen-fixing bacterial strains were isolated from 3 rhizosphere soil samples taken from mangrove plants in the Dongzhaigang National Mangrove Nature Reserve of China. Most isolates belonged to Gammaproteobacteria Pseudomonas, showing that these environments constituted favorable niches for such abundant nitrogen-fixing bacteria. New members of the diazotrophs were also found. Using a soil DNA extraction and PCR-cloning-sequencing approach, 135 clones were analyzed by restriction fragment length polymorphism (RFLP) analysis, and 27 unique nifH sequence phylotypes were identified, most of which were closely related to sequences from uncultured bacteria. The diversity of nitrogen-fixing bacteria was assessed by constructing nifH phylogenetic trees from sequences of all isolates and clones in this work, together with related nifH sequences from other mangrove ecosystems in GenBank. The nifH diversity varied among soil samples, with distinct biogeochemical properties within a mangrove ecosystem. When comparing different mangrove ecosystems, the nifH gene sequences from a specific site tended to cluster as individual groups. The results provided interesting data and novel information on our understanding of diazotroph community diversity in the mangrove ecosystems.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

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)0.0010.000

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 head0.005
GPT teacher head0.153
Teacher spread0.148 · 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.

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

Citations35
Published2012
Admission routes1
Has abstractyes

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