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Record W2278704345 · doi:10.2166/wst.2003.0149

A comparitive study of ammonia-oxidizing bacteria in lab-scale industrial wastewater treatment reactors

2003· article· en· W2278704345 on OpenAlexaff
Arlene K. Rowan, Gleyci Aparecida Oliveira Moser, N. F. Gray, Jason Snape, David Fearnside, Thomas P. Curtis, Michael R. Barer, Ian M. Head

Bibliographic record

VenueWater Science & Technology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsAstraZeneca (Canada)
FundersAstraZeneca
KeywordsNitrosomonasTemperature gradient gel electrophoresisBiologyIndustrial wastewater treatmentWastewaterEffluentBacteria16S ribosomal RNASewage treatmentEcologyEnvironmental scienceEnvironmental engineeringGeneticsNitriteNitrate

Abstract

fetched live from OpenAlex

The diversity and community structure of the beta-proteobacterial ammonia oxidising bacteria (AOB) in a range of different lab-scale industrial wastewater treatment reactors were compared. Three of the reactors treat waste from mixed domestic and industrial sources whereas the other reactor treats waste solely of industrial origin. PCR with AOB selective primers was combined with denaturing gradient ge electrophoresis to allow comparative analysis of the dominant AOB populations and the phylogenetic affiliation of the dominant AOB was determined by cloning and sequencing or direct sequencing of bands excised from DGGE gels. Different AOB were found within and between different reactors. All AOB sequences identified were grouped within the genus Nitrosomonas. Within the lab-scale reactors there appeared to be selection for a low diversity of AOB and predominance of a single AOB population. Furthermore, the industrial input in both effluents apparently selected for salt tolerant AOB, most closely related to Nitrosococcus mobilis and Nitrosomonas halophila.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.024
GPT teacher head0.239
Teacher spread0.214 · 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

Citations21
Published2003
Admission routes1
Has abstractyes

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