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Record W4362673363 · doi:10.1038/s41597-023-02069-3

Author Correction: GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

2023· erratum· en· W4362673363 on OpenAlexaff
Moritz K. Lehmann, Daniela Gurlin, Nima Pahlevan, Krista Alikas, Ted Conroy, Janet Anstee, Sundarabalan V. Balasubramanian, Cláudio Clemente Faria Barbosa, Caren Binding, Astrid Bracher, Mariano Bresciani, Ashley M. Burtner, Zhigang Cao, Arnold G. Dekker, Courtney A. Di Vittorio, Nathan Drayson, Reagan M. Errera, Virginia Laura Fernández, Dariusz Ficek, Cédric G. Fichot, Peter Gege, Claudia Giardino, Anatoly A. Gitelson, Steven R. Greb, Hayden Henderson, Hiroto HIGA, Abolfazl Irani Rahaghi, Cédric Jamet, Dalin Jiang, Thomas Jordan, Kersti Kangro, Jeremy A. Kravitz, Arne S. Kristoffersen, Raphael M. Kudela, Lin Li, Martin Ligi, Hubert Loisel, Steven E. Lohrenz, Ronghua Ma, Daniel Andrade Maciel, Tim Malthus, Bunkei Matsushita, Mark A. Matthews, Camille Minaudo, Deepak R. Mishra, Sachidananda Mishra, Tim Moore, Wesley J. Moses, Nguyễn Thị Thu Hà, Evlyn Márcia Leão de Moraes Novo, Stéfani Novoa, Daniel Odermatt, David M. O’Donnell, Leif G. Olmanson, Michael Ondrusek, Natascha Oppelt, Sylvain Ouillon, Waterloo Pereira Filho, Stefan Plattner, Antonio Ruiz Verdú, Salem Ibrahim Salem, John F. Schalles, Stefan Simis, Eko Siswanto, Brandon Smith, Ian Somlai-Schweiger, Mariana Altenburg Soppa, Evangelos Spyrakos, Elinor Tessin, H.J. van der Woerd, Andrea Vander Woude, Ryan Vandermeulen, Vincent Vantrepotte, Marcel Robert Wernand, Mortimer Werther, Kyana Young, Linwei Yue

Bibliographic record

VenueScientific Data · 2023
Typeerratum
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsHyperspectral imagingIn situRemote sensingEnvironmental scienceWater qualityQuality (philosophy)GeographyBiologyPhysicsEcologyMeteorology

Abstract

fetched live from OpenAlex

An author of the paper was omitted in the original version (Ted Conroy, University of Waikato, New Zealand). This has been corrected in the pdf and HTML versions of the paper, and the associated metadata.

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)0.003
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.117
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.1170.087

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 head0.126
GPT teacher head0.388
Teacher spread0.263 · 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 designNot applicable
Domainnot available
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

Citations4
Published2023
Admission routes1
Has abstractyes

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