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Record W3119083026 · doi:10.1038/s41588-021-00780-8

Author Correction: Mutations disrupting neuritogenesis genes confer risk for cerebral palsy

2021· article· en· W3119083026 on OpenAlexaff
Sheng Chih Jin, Sara A. Lewis, Somayeh Bakhtiari, Xue Zeng, Michael C. Sierant, Sheetal Shetty, Sandra M. Nordlie, Aureliane Elie, Mark Corbett, Bethany Y. Norton, Clare L. van Eyk, Shozeb Haider, Brandon S. Guida, Helen Magee, James Liu, Stephen F. Pastore, John B. Vincent, Janice Brunstrom-Hernandez, Antigone Papavasileiou, Michael Fahey, Jesia G. Berry, Kelly Harper, Chongchen Zhou, Junhui Zhang, Boyang Li, Hongyu Zhao, Jennifer Heim, Dani L. Webber, Mahalia S. B. Frank, Lei Xia, Yiran Xu, Dengna Zhu, Bohao Zhang, Amar H. Sheth, James Knight, Christopher Castaldi, Irina R. Tikhonova, Francesc López‐Giráldez, Boris Keren, Sandra Whalen, Julien Buratti, Diane Doummar, Megan Cho, Kyle Retterer, Francisca Millan, Yangong Wang, Jeff L. Waugh, Lance H. Rodan, Julie S. Cohen, Ali Fatemi, Angela E. Lin, J. P. Phillips, Timothy Feyma, Suzanna C. MacLennan, Spencer Vaughan, Kylie Crompton, Susan Reid, Dinah Reddihough, Qing Shang, Chao Gao, Iona Novak, Nadia Badawi, Yana A. Wilson, Sarah McIntyre, Shrikant Mane, Xiaoyang Wang, David J. Amor, Daniela C. Zarnescu, Qiongshi Lu, Qinghe Xing, Changlian Zhu, Kaya Bilgüvar, Sergio Padilla‐Lopez, Richard P. Lifton, Jozef Gécz, Alastair H. MacLennan, Michael C. Kruer

Bibliographic record

VenueNature Genetics · 2021
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsBiologyCerebral palsyGeneGeneticsPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
metaresearch head score (Gemma)0.034
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 score0.055
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.034
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0110.008
Insufficient payload (model declined to judge)0.0550.020

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 head0.020
GPT teacher head0.311
Teacher spread0.292 · 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

Citations5
Published2021
Admission routes1
Has abstractno

Explore more

Same venueNature GeneticsSame topicCerebral Palsy and Movement DisordersFrench-language works237,207