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Record W2944548763 · doi:10.1038/s41564-019-0426-5

Global diversity and biogeography of bacterial communities in wastewater treatment plants

2019· article· en· W2944548763 on OpenAlexaff
Daliang Ning, Bing Zhang, Yong Li, Mathew R. Brown, Zhenxin Li, Joy D. Van Nostrand, Fangqiong Ling, Naijia Xiao, Ya Zhang, Julia Vierheilig, George Wells, Yunfeng Yang, Ye Deng, Qichao Tu, Aijie Wang, Dany Acevedo, M. Agulló-Barceló, Pedro J. J. Alvarez, Lisa Alvarez‐Cohen, Gary L. Andersen, Juliana Calábria de Araújo, Kevin F. Boehnke, Philip L. Bond, Charles Bott, Patricia Bovio-Winkler, Rebecca K. Brewster, Faizal Bux, Angela Cabezas, Léa Cabrol, Si Chen, Craig S. Criddle, Ye Deng, Claudia Etchebehere, Amanda K. Ford, Dominic Frigon, Janeth Sanabria, James S. Griffin, April Z. Gu, Moshe Habagil, Lauren Hale, Steven D. Hardeman, Marc Harmon, Harald Horn, Zhiqiang Hu, Shameem Jauffur, David R. Johnson, Jürg Keller, Alexander Keucken, Sheena Kumari, Cíntia Dutra Leal, Laura Lebrun, Jangho Lee, Zarraz May Ping Lee, Mengyan Li, Xu Li, Yu Liu, Richard G. Luthy, Lêda C. Mendonça-Hagler, Francisca Gleire Rodriguez de Menezes, A. J. Meyers, Amin Mohebbi, Adrian Oehmen, Andrew Palmer, Prathap Parameswaran, Joonhong Park, Deborah Patsch, Valéria Reginatto, Bruce E. Rittmann, Adalberto Noyola, Simona Rossetti, Jatinder Sidhu, William T. Sloan, Kylie Smith, Oscarina Viana de Sousa, David A. Stahl, Kyle Stephens, Renmao Tian, Nicholas B. Tooker, Daniel de los Cobos‐Vasconcelos, Michael Wagner, Steven A. Wakelin, Bei Wang, Joseph E. Weaver, Stephanie West, Paul Wilmes, Sung-Geun Woo, Jer‐Horng Wu, Liyou Wu, Chuanwu Xi, Meiying Xu, Tao Yan, Min Yang, Michelle Young, Haowei Yue, Tong Zhang, Qian Zhang, Wen Zhang, Yu Zhang, Hongde Zhou, Jizhong Zhou, Xianghua Wen, Thomas P. Curtis, Qiang He, Zhili He

Bibliographic record

VenueNature Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of GuelphConcordia UniversityMcGill University
FundersGuangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation TechnologyUniversidade Federal do Rio de JaneiroApplied Molecular Biosciences UnitNational Cheng Kung UniversityFaculdade de Ciências e Tecnologia, Universidade Nova de LisboaUniversidade Nova de LisboaUniversidad Nacional Autónoma de MéxicoUniversidade de São PauloNorth Carolina State UniversityChinese Academy of SciencesResearch Center for Eco-Environmental Sciences, Chinese Academy of SciencesCommonwealth Scientific and Industrial Research OrganisationTsinghua UniversityInstituto de Ingeniería, Universidad Nacional Autónoma de MéxicoUniversity of GlasgowLawrence Berkeley National LaboratoryRede de Química e TecnologiaVillum FondenNewcastle UniversityNorthern Arizona UniversityUniversity of OklahomaSun Yat-sen UniversityArizona State University
KeywordsEcologyActivated sludgeBiologyBiological dispersalSewage treatmentMicrobial ecologyBiogeographyMicrobial population biologyEnvironmental scienceEnvironmental engineeringBacteriaPopulation

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations896
Published2019
Admission routes1
Has abstractno

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