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Record W3175253421 · doi:10.1038/s41380-021-01191-1

Correction: Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

2021· erratum· en· W3175253421 on OpenAlexaff
Nils Opel, Anbupalam Thalamuthu, Yuri Milaneschi, Dominik Grotegerd, Claas Flint, Ramona Leenings, Janik Goltermann, Maike Richter, Tim Hahn, Georg Woditsch, Klaus Berger, Marco Hermesdorf, Andrew M. McIntosh, Heather C. Whalley, Mathew A. Harris, Frank P. MacMaster, Henrik Walter, Ilya M. Veer, Thomas Frodl, Angela Carballedo, Axel Krug, Igor Nenadić, Tilo Kircher, André Alemán, Nynke A. Groenewold, Dan J. Stein, Jair C. Soares, Giovana Zunta‐Soares, Benson Mwangi, Mon‐Ju Wu, Martin Walter, Meng Li, Ben J. Harrison, Christopher G. Davey, Kathryn R. Cullen, Bonnie Klimes‐Dougan, Bryon A. Mueller, Philipp G. Sämann, Brenda W.J.H. Penninx, Laura Nawijn, Dick J. Veltman, Lyubomir I. Aftanas, И. В. Брак, Elena Filimonova, Evgeniy A. Osipov, Liesbeth Reneman, Anouk Schrantee, Hans J. Grabe, Sandra Van der Auwera, Katharina Wittfeld, Norbert Hosten, Henry Völzke, Kang Sim, Ian H. Gotlib, Matthew D. Sacchet, Jim Lagopoulos, Sean N. Hatton, Ian B. Hickie, Elena Pozzi, Paul M. Thompson, Neda Jahanshad, Lianne Schmaal, Bernhard T. Baune, Udo Dannlowski

Bibliographic record

VenueMolecular Psychiatry · 2021
Typeerratum
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsAlberta HealthUniversity of Calgary
Fundersnot available
KeywordsPsychiatryObesityMedicinePsychologyRelation (database)Clinical psychologyBioinformaticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

The article “Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders”, written by Nils Opel, Anbupalam Thalamuthu, Yuri Milaneschi, Dominik Grotegerd, Claas Flint, Ramona Leenings, Janik Goltermann, Maike Richter, Tim Hahn, Georg Woditsch, Klaus Berger, Marco Hermesdorf, Andrew McIntosh, Heather C. Whalley, Mathew A. Harris, Frank P. MacMaster, Henrik Walter, Ilya M. Veer, Thomas Frodl, Angela Carballedo, Axel Krug, Igor Nenadic, Tilo Kircher, Andre Aleman, Nynke A. Groenewold, Dan J. Stein, Jair C. Soares, Giovana B. Zunta-Soares, Benson Mwangi, Mon-Ju Wu, Martin Walter, Meng Li, Ben J. Harrison, Christopher G. Davey, Kathryn R. Cullen, Bonnie Klimes-Dougan, Bryon A. Mueller, Philipp G. Sämann, Brenda Penninx, Laura Nawijn, Dick J. Veltman, Lyubomir Aftanas, Ivan V. Brak, Elena A. Filimonova, Evgeniy A. Osipov, Liesbeth Reneman, Anouk Schrantee, Hans J. Grabe, Sandra Van der Auwera, Katharina Wittfeld, Norbert Hosten, Henry Völzke, Kang Sim, Ian H. Gotlib, Matthew D. Sacchet, Jim Lagopoulos, Sean N. Hatton, Ian Hickie, Elena Pozzi, Paul M. Thompson, Neda Jahanshad, Lianne Schmaal, Bernhard T. Baune & Udo Dannlowski, was originally published electronically on the publisher’s internet portal on 28 May 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 4 June 2021 to © The Author(s) 2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0 . Open Access funding enabled and organized by Projekt DEAL.

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)0.005
metaresearch head score (Gemma)0.093
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.184
Threshold uncertainty score0.614

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.093
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.1840.048

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 head0.003
GPT teacher head0.231
Teacher spread0.228 · 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
GenreEditorial

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

Citations15
Published2021
Admission routes1
Has abstractyes

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