Author Correction: MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants
Bibliographic record
Abstract
Authors and Affiliations Center for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark Morten Kam Dahl Dueholm, Marta Nierychlo, Kasper Skytte Andersen, Vibeke Rudkjøbing, Simon Knutsson, Per H. Nielsen, Mads Albertsen & Per Halkjær Nielsen Environmental Science Department, The Institute for Scientific and Technological Research of San Luis Potosi (IPICYT), San Luis Potosí, Mexico Sonia Arriaga Department of Process, Energy and Environmental Technology, University College of Southeast Norway, Porsgrunn, Norway Rune Bakke Center for Microbial Ecology and Technology, Ghent University, Ghent, Belgium Nico Boon Institute for Water and Wastewater Technology, Durban University of Technology, Durban, South Africa Faizal Bux & Sheena Kumari Veolia Water Technologies AB, AnoxKaldnes, Lund, Sweden Magnus Christensson Department Of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia Adeline Seak May Chua Environmental Engineering, Newcastle University, Newcastle, England Thomas P. Curtis The Cytryn Lab, Microbial Agroecology, Volcani Center, Agricultural Research Organization, Rishon Lezion, Israel Eddie Cytryn INGEBI-CONICET, University of Buenos Aires, Buenos Aires, Argentina Leonardo Erijman Department of Biochemistry and Microbial Genetics, Biological Research Institute “Clemente Estable”, Montevideo, Uruguay Claudia Etchebehere NIREAS-International Water Research Center, University of Cyprus, Nicosia, Cyprus Despo Fatta-Kassinos Environmental Engineering, McGill University, Montreal, QC, Canada Dominic Frigon School of Microbiology, Universidad de Antioquia, Medellín, Colombia Maria Carolina Garcia-Chaves School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA April Z. Gu Water Chemistry and Water Technology and DVGW Research Laboratories, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Harald Horn David Jenkins & Associates, Inc, Kensington, CA, USA David Jenkins Institute for Water Quality and Resource Management, TU Wien, Vienna, Austria Norbert Kreuzinger Water Innovation and Research Centre, University of Bath, Bath, England Ana Lanham Singapore Centre of Environmental Life Sciences Engineering (SCELSE) Nanyang Technological University, Singapore, Singapore Yingyu Law Water Desalination and Reuse Center, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia TorOve Leiknes Process Engineering in Urban Water Management, ETH Zürich, Zürich, Switzerland Eberhard Morgenroth Department of Biology, Warsaw University of Technology, Warsaw, Poland Adam Muszyński Environmental Microbial Genetics Lab, La Trobe University, Melbourne, VIC, Australia Steve Petrovski Technologies and Evaluation Area, Catalan Institute for Water Research, ICRA, Girona, Spain Maite Pijuan VA Tech Wabag Ltd, Chennai, India Suraj Babu Pillai Biochemical Engineering Group, Universidade Nova de Lisboa, Lisboa, Portugal Maria A. M. Reis State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China Qi Rong Water Research Institute IRSA - National Research Council (CNR), Rome, Italy Simona Rossetti La Trobe University, Melbourne, VIC, Australia Robert Seviour Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, MA, USA Nick Tooker Kemira Oyj, Espoo R&D Center, Espo, Finland Pirjo Vainio Environmental Biotechnology, TU Delft, Delft, The Netherlands Mark van Loosdrecht VA Tech Wabag, Philippines Inc., Makati City, Philippines R. Vikraman Department of Water Technology and Environmental Engineering, University of Chemistry and Technology, Prague, Czech Republic Jiří Wanner Environmental Life Science Engineering, TU Delft, Delft, The Netherlands David Weissbrodt School of Environment, Tsinghua University, Beijing, China Xianghua Wen Environmental Biotechnology Lab, Department of Civil Engineering, The University of Hong Kong, Hong Kong, Hong Kong Tong Zhang Authors Morten Kam Dahl Dueholm View author publications You can also search for this author in PubMed Google Scholar Marta Nierychlo View author publications You can also search for this author in PubMed Google Scholar Kasper Skytte Andersen View author publications You can also search for this author in PubMed Google Scholar Vibeke Rudkjøbing View author publications You can also search for this author in PubMed Google Scholar Simon Knutsson View author publications You can also search for this author in PubMed Google Scholar Mads Albertsen View author publications You can also search for this author in PubMed Google Scholar Per Halkjær Nielsen View author publications You can also search for this author in PubMed Google Scholar Consortia MiDAS Global Consortium Sonia Arriaga , Rune Bakke , Nico Boon , Faizal Bux , Magnus Christensson , Adeline Seak May Chua , Thomas P. Curtis , Eddie Cytryn , Leonardo Erijman , Claudia Etchebehere , Despo Fatta-Kassinos , Dominic Frigon , Maria Carolina Garcia-Chaves , April Z. Gu , Harald Horn , David Jenkins , Norbert Kreuzinger , Sheena Kumari , Ana Lanham , Yingyu Law , TorOve Leiknes , Eberhard Morgenroth , Adam Muszyński , Steve Petrovski , Maite Pijuan , Suraj Babu Pillai , Maria A. M. Reis , Qi Rong , Simona Rossetti , Robert Seviour , Nick Tooker , Pirjo Vainio , Mark van Loosdrecht , R. Vikraman , Jiří Wanner , David Weissbrodt , Xianghua Wen , Tong Zhang & Per H. Nielsen Corresponding authors Correspondence to Morten Kam Dahl Dueholm or Per Halkjær Nielsen .
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.078 | 0.063 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".