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Record W4413414210 · doi:10.1038/s42003-025-08714-4

Publisher Correction: fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience

2025· erratum· en· W4413414210 on OpenAlexaff
Meryem A. Yücel, Robert Luke, Rickson C. Mesquita, Alexander von Lühmann, David M. A. Mehler, Michael Lührs, Jessica Gemignani, Androu Abdalmalak, Franziska Albrecht, Iara de Almeida Ivo, Christina Artemenko, Kira Ashton, Paweł Augustynowicz, Aahana Bajracharya, Élise Bannier, Beatrix Barth, Laurie Bayet, Jacqueline Behrendt, Hadi Borjkhani, Lenaic Borot, Jordan A. Borrell, Sabrina Brigadoi, Kolby Brink, Chiara Bulgarelli, Emmanuel Caruyer, Hsin‐Chin Chen, Christopher Copeland, Isabelle Corouge, Simone Cutini, Renata Di Lorenzo, Thomas Dresler, Adam T. Eggebrecht, Ann‐Christine Ehlis, Sinem Burcu Erdoğan, Daniëlle Evenblij, Talukdar Raian Ferdous, Victoria Fracalossi, Erika Franzén, Anne Gallagher, Christian Gerloff, Judit Gervain, Noy Goldhamer, Louisa K. Gossé, Ségolène M. R. Guérin, Edgar Guevara, S. M. Hadi Hosseini, Hamish Innes-Brown, Isabell Int-Veen, Sagi Jaffe‐Dax, Nolwenn Jégou, Hiroshi Kawaguchi, Caroline Kelsey, M. Kent, Roman Kessler, Nadeen Kherbawy, Franziska Klein, Nofar Kochavi, Matthew Kolisnyk, Yogev Koren, Agnes Kroczek, Alexander Kvist, Chen-Hao P. Lin, Andreas Löw, Siying Luan, Darren Mao, Giovani Grisotti Martins, Eike Middell, Samuel Montero‐Hernández, Murat Can Mutlu, Sergio L. Novi, Natacha Paquette, Ishara Paranawithana, Yisrael Parmet, Jonathan E. Peelle, Ke Peng, Tommy Peng, João Pereira, Paola Pinti, Luca Pollonini, Ali Rahimpour Jounghani, Vanessa Reindl, Wiebke Ringels, Betti Schopp, Alina Schulte, Martin Schulte‐Rüther, Ari Segel, Tirdad Seifi, Maureen J. Shader, Hadas Shavit, Arefeh Sherafati, Mojtaba Soltanlou, Bettina Sorger, Emma Speh, Kevin Stubbs, Katharina Stute, Eileen Sullivan, Sungho Tak, Zeus Tipado, Julie Tremblay, Homa Vahidi, Maaike Van Eeckhoutte, Phetsamone Vannasing, Grégoire Vergotte, Marion Vincent, Eileen Oberwelland Weiß, Dalin Yang, Gülnaz Yükselen, Dariusz Zapała, Vit Zemanek

Bibliographic record

VenueCommunications Biology · 2025
Typeerratum
Languageen
FieldEnvironmental Science
TopicHydrological Forecasting Using AI
Canadian institutionsLondon Health Sciences CentreUniversité de MontréalUniversity of ManitobaWestern University
Fundersnot available
KeywordsReproducibilityQuality (philosophy)Pipeline transportComputer scienceData qualityData scienceStatisticsEngineeringMathematicsMechanical engineeringOperations managementPhilosophyEpistemology

Abstract

fetched live from OpenAlex

In this article, Meryem A. Yücel should have been denoted as a co-corresponding author. The original article has been corrected.

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)0.010
metaresearch head score (Gemma)0.144
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.144
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0050.004
Scholarly communication0.0070.003
Open science0.0030.003
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0720.054

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 head0.199
GPT teacher head0.420
Teacher spread0.221 · 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.

Study designObservational
DomainReproducibility
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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