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
Notice bibliographique
Résumé
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 .
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,078 | 0,063 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».