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Record W2040168020 · doi:10.1139/w08-011

Seasonal variation in communities of ammonia-oxidizing bacteria based on polymerase chain reaction – denaturing gradient gel electrophoresis in a biofilm reactor for drinking water pretreatment

2008· article· en· W2040168020 on OpenAlexvenueno aff
Xiaowen Zhang, Yingying Qin, Hongqiang Ren, Dao-Tang Li, Hong Yang

Bibliographic record

VenueCanadian Journal of Microbiology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
Fundersnot available
KeywordsTemperature gradient gel electrophoresisNitrosomonasLibraryBacteriaNitrosomonas europaeaAmmoniaBiology16S ribosomal RNAMicrobiologyGel electrophoresisCanonical correspondence analysisMicrobial population biologyNitrificationEnvironmental chemistryChemistryBiochemistryEcologyNitriteGeneticsNitrateNitrogen

Abstract

fetched live from OpenAlex

The diversity and variation of total and active ammonia-oxidizing bacteria in a full-scale aerated submerged biofilm reactor for drinking water pretreatment were characterized by clone libraries and denaturing gradient gel electrophoresis (DGGE) analysis of 16S rRNA and its gene during a whole year. Sequences obtained from clone libraries affiliated with the Nitrosomonas oligotropha lineage and the Nitrosomonas communis lineage. An uncultured subgroup of Nitrosomonas communis lineage was also detected. Seasonal variations in both total and active ammonia-oxidizing bacteria communities were observed in the DGGE profiles, but an RNA-based analysis reflected more obvious dynamic changes in ammonia-oxidizer community than a DNA-based approach. Statistical study based on canonical correspondence analysis showed that a community shift of active ammonia oxidizers was significantly influenced by temperature and pH, but no significant correlation was found between environmental variables and total ammonia-oxidizer community shift.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.186
Teacher spread0.176 · 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 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

Citations9
Published2008
Admission routes1
Has abstractyes

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