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Record W4394691377 · doi:10.1038/s41467-024-47545-5

Author Correction: Using rare genetic mutations to revisit structural brain asymmetry

2024· erratum· en· W4394691377 on OpenAlexaffabout
Jakub Kopál, Kuldeep Kumar, Kimia Shafighi, Karin Saltoun, Claudia Modenato, Clara Moreau, Guillaume Huguet, Martineau Jean‐Louis, Charles-Olivier Martin, Zohra Saci, Nadine Younis, Élise Douard, Khadijé Jizi, Alexis Beauchamp-Châtel, Leila Kushan, Ana Isabel Silva, Marianne B. M. van den Bree, David E.J. Linden, Michael J. Owen, Jérémy Hall, Sarah Lippé, Bogdan Draganski, Ida E. Sønderby, Ole A. Andreassen, David C. Glahn, Paul M. Thompson, Carrie E. Bearden, Robert J. Zatorre, Sébastien Jacquemont, Danilo Bzdok

Bibliographic record

VenueNature Communications · 2024
Typeerratum
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsInternational Laboratory for Brain, Music and Sound ResearchUniversité de MontréalInstitut universitaire en santé mentale de MontréalMcGill UniversityCentre Hospitalier Universitaire Sainte-JustineMontreal Neurological Institute and HospitalMila - Quebec Artificial Intelligence Institute
Fundersnot available
KeywordsMutationAsymmetryComputational biologyGeneticsComputer scienceBiologyGenePhysics

Abstract

fetched live from OpenAlex

In this article the affiliation details for Robert Zatorre were incorrectly given as ‘Department of Pediatrics, University of Montréal, Montréal, Quebec, Canada.’ but should have been ‘TheNeuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Faculty of Medicine, McGill University, Montreal, QC, Canada’. 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)0.003
metaresearch head score (Gemma)0.051
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 score0.049
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.051
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0490.023

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 head0.053
GPT teacher head0.391
Teacher spread0.339 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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