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Record W3194590544 · doi:10.1186/s13059-021-02468-y

Author Correction: Community-wide hackathons to identify central themes in single-cell multi-omics

2021· erratum· en· W3194590544 on OpenAlexaff
Kim‐Anh Lê Cao, Al J. Abadi, Emily F. Davis-Marcisak, Lauren Hsu, Arshi Arora, Alexis Coullomb, Atul Deshpande, Yuzhou Feng, Pratheepa Jeganathan, Melanie Loth, Chen Meng, Wancen Mu, Véra Pancaldi, Kris Sankaran, Dario Righelli, Amrit Singh, Joshua Sodicoff, Genevieve Stein-O’Brien, Ayshwarya Subramanian, Joshua D. Welch, Yue You, Ricard Argelaguet, Vincent J. Carey, Ruben Dries, Casey S. Greene, Susan Holmes, Michael I. Love, Matthew E. Ritchie, Guo‐Cheng Yuan, Aedín C. Culhane, Elana J. Fertig

Bibliographic record

VenueGenome biology · 2021
Typeerratum
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of British ColumbiaPrevention of Organ FailureMcMaster University
FundersNational Institute of Neurological Disorders and StrokeNational Human Genome Research Institute
KeywordsBiologyGenome BiologyHuman geneticsOmicsComputational biologyData scienceEvolutionary biologyGenomicsBioinformaticsGeneticsComputer scienceGenomeGene

Abstract

fetched live from OpenAlex

Following publication of the original article [1], the authors identified that author Dario Righelli had erroneously been omitted from the author panel. The author group above has been updated and the original article [1] 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)0.009
metaresearch head score (Gemma)0.142
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 score0.080
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.142
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0050.003
Scholarly communication0.0060.003
Open science0.0040.004
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0800.053

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 head0.034
GPT teacher head0.273
Teacher spread0.239 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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