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Record W4319063022 · doi:10.1038/s41467-023-36264-y

Author Correction: Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

2023· erratum· en· W4319063022 on OpenAlexaff
Roser Corominas, Xinping Yang, Guan Ning Lin, Shuli Kang, Yun Shen, Lila Ghamsari, Martin Broly, Maria Rodriguez, Stanley Tam, Shelly A. Wanamaker, Changyu Fan, S. Stephen Yi, Murat Taşan, Irma Lemmens, Xingyan Kuang, Nan Zhao, Dheeraj Malhotra, Jacob J. Michaelson, Vladimir Vacic, Michael A. Calderwood, Frederick P. Roth, Jan Tavernier, Steve Horvath, Kourosh Salehi‐Ashtiani, Dmitry Korkin, Jonathan Sebat, David E. Hill, Tong Hao, Marc Vidal, Lilia M. Iakoucheva

Bibliographic record

VenueNature Communications · 2023
Typeerratum
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsGene isoformAutismNeuroscienceComputational biologyBiologyGeneticsBioinformaticsComputer scienceMedicineGenePsychiatry

Abstract

fetched live from OpenAlex

Since the publication of this work, Shelly A. Wanamaker has changed their name from Shelly A. Trigg. This has now been amended.

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)0.091
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 score0.065
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.091
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0650.036

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 head0.019
GPT teacher head0.301
Teacher spread0.282 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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