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Author Correction: A roadmap for equitable reuse of public microbiome data
Laura A. Hug, Roland Hatzenpichler, Cristina Moraru, André Soares, Folker Meyer, Anke Heyder, Rabab Mahmoud Abdallah, A. Abdalrahem, Nafi’u Abdulkadir, Ibukun M. Adesiyan, L. Alteio, Karthik Anantharaman, R. Anderson, A. H. Andrei, J. Antonio Baeza, Frederik Bak, Brett J. Baker, Alexander Bartholomäus, Nicolás Bejerman, Jennifer F. Biddle, Andrew Bissett, J. Blakeley-Ruiz, K. A. Block, Joachim Boldt, Germán Bonilla‐Rosso, Till L. V. Bornemann, Verena S. Brauer, William J. Brazelton, Andreas Bremges, Elena Buelow, Zachary M. Burcham, Annabel Cansdale, J. Gregory Caporaso, Tomislav Cernava, Ioanna Chatzigiannidou, Rodrigo Costa, Cameron R. Currie, Anne Daebeler, V. De Anda, Ana de Santiago, Luísa Mayumi Arake de Tacca, Justine W. Debelius, Simon M. Dittami, Xu Dong, Mária Džunková, Arwyn Edwards, Robert A. Edwards, Susan Egbert, Julia C. Engelmann, Thijs J. G. Ettema, Cassandra L. Ettinger, Aleksandra Petrović Fabijan, Rebecca Ferguson, Patrizia Ferretti, Pierre Foucault, Jed A. Fuhrman, Andreas Gada, Patricia Geesink, Isabel Rodrigues Gerhardt, Mark O. Gessner, Donato Giovannelli, David I. Gittins, Gregory B. Gloor, Raúl A. González‐Pech, Chandana Gopalakrishnappa, Chris Greening, Rachel Gregor, Ann Gregory, Hans‐Peter Grossart, Mathieu Groussin, Bruno V. Guerrero, Mustafa Güzel, Natsuko Hamamura, Trinity L. Hamilton, Jon Hamm, Luke Hart, Christiane Hassenrück, Melanie Hay, Robert M. Hechler, Patrick Hellwig, Michael A. Henson, Michael Herold, Poppy Hesketh-Best, Matthias Hess, Luke S. Hillary, Thomas C. A. Hitch, Sai Suresh Hivarkar, Katharina J. Hoff, Erik Hom, Shengwei Hou, Luisa W. Hugerth, Yeongwoo Hwang, Nicholas E. Ilott, Zackary J. Jay, Sean P. Jungbluth, Elham Karimi, Y. M. Kaspareit, Ciara Keating, Matthew Kellom, E. Anders Kiledal, Ingeborg J. Klarenberg, Robert J. Knight, Angela Koech, Eugene V. Koonin, Konstantinos Ar. Kormas, Katharina Kujala, Nikos C. Kyrpides, Sabina Leanti La Rosa, Cédric C. Laczny, Kevin K. Lahmers, Xianyong Lan, A. A. Lateef, S. H. Lau, Florian Leese, María Ángeles Lezcano, S. S. Li, Rayane Nunes Lima, Sebastian Lücker, Alexander Mahnert, Sina Majidian, Lukas Malfertheiner, Andrew J. Marshall, Sean Meaden, Conor J. Meehan, Dimitri V. Meier, Chrats Melkonian, Daniel R. Mende, Julie L. Meyer, Grégoire Michoud, Vladimir Mikryukov, Samuel Miravet‐Verde, Jan Muschiol, Muhammad Kabiru Nata’ala, Josh D. Neufeld, Sigrid Neuhauser, Olayinka Osuolale, Jay Osvatic, Katherine M. Pappas, Daniel Parks, Renate Parry, P. V. Pascoal, Christina Pavloudi, Brent Peyton, Julia Plewka, Mathilde Poyet, Taylor Priest, E. K. Quaye, Thomas Rattei, Philipp Rausch, Elíbio Rech, Christian Rinke, Carol Robinson, Alejandro Rodríguez-Gijón, Luis M. Rodriguez‐R, Robin R. Rohwer, Tim Roloff, Jennifer Rothman, Sonja Rückert, S. Emil Ruff, Jasmine Saini, Michel Geovanni Santiago‐Martínez, Luciana F. Santoferrara, Mohamed S. Sarhan, Jimmy H. Saw, Tomasa Sbaffi, Ralf B. Schäfer, George A. Schaible, Michael Schloter, Ruth A. Schmitz, Carsten J. Schubert, Oliver Schwengers, Luděk Sehnal, A. Chandrasekar, Jegan Sekar, Mitiku Mihiret Seyoum, Manesh Shah, Itai Sharon, Bettina Siebers, Ella T. Sieradzki, Dimitrios Skliros, Oona Snoeyenbos-West, Adam Sorbie, Daan R. Speth, C. Grace Sprehn, Pranay Srivastava, Tom L. Stach, Jason Stajich, Jeffrey R. Starke, Andrew D. Steen, Richard Stöckl, T. Stoikidou, Nejc Stopnišek, Rohan Sukumaran, Bernd Sures, Shino Suzuki, Daniel Tamarit, Patrick H. Thieringer, R. Y. Tito, Chetan Trivedi, Gareth Trubl, Jaak Truu, Myrto Tsiknia, Juan A. Ugalde, Luis E. Valentin-Alvarado, Xabier Vázquez-Campos, Julia Vierheilig, F. A. Bastiaan von Meijenfeldt, Michael Wagner, Calum J. Walsh, Shuqiang Wang, Yue Wang, Carl‐Eric Wegner, Tiffany L. Weir, L. Weiss, JL Weissman, Antje Wichels, Candace L. Williams, Travis Williams, Alexandra Z. Worden, Tanja Woyke, Mengxiong Wu, Wei Xiu, Ying Zhang, Jun Zhu, Ryan Ziels, Benjamin Zwirzitz, Alexander J. Probst
Bibliographic record
VenueNature Microbiology · 2025
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryWestern UniversityUniversity of TorontoMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsParagraphConfidentialityReuseMicrobiomeHuman immunodeficiency virus (HIV)Public involvementPublic health
Abstract
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.445
Threshold uncertainty score0.999
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.114
GPT teacher head0.411
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation status
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; both teacher heads agree on what is shown here.
Study designNot applicable
Domainnot available
GenreMethods
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
Citations0
Published2025
Admission routes1
Has abstractno