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Record W3205508855 · doi:10.1038/s41580-021-00428-9

Author Correction: Guidelines and definitions for research on epithelial–mesenchymal transition

2021· review· en· W3205508855 on OpenAlexaff
Jing Yang, Parker B. Antin, Geert Berx, Cédric Blanpain, Thomas Brabletz, Marianne Bronner‐Fraser, Kyra Campbell, Amparo Cano, Jordi Casanova, Gerhard Christofori, Shoukat Dedhar, Rik Derynck, Heide L. Ford, Jonas Fuxe, Antonio García de Herreros, Gregory J. Goodall, Anna‐Katerina Hadjantonakis, Ruby Yun‐Ju Huang, Chaya Kalcheim, Raghu Kalluri, Yibin Kang, Yeesim Khew‐Goodall, Herbert Levine, Jinsong Liu, Gregory D. Longmore, Sendurai A. Mani, Joan Massagué, Roberto Mayor, David R. McClay, Keith E. Mostov, Donald F. Newgreen, M. Ángela Nieto, Alain Puisieux, Raymond B. Runyan, Pierre Savagner, Ben Z. Stanger, Marc P. Stemmler, Yoshiko Takahashi, Masatoshi Takeichi, Eric Théveneau, Jean Paul Thiery, Erik W. Thompson, Robert A. Weinberg, Elizabeth D. Williams, Jianhua Xing, Binhua P. Zhou, Guojun Sheng

Bibliographic record

VenueNature Reviews Molecular Cell Biology · 2021
Typereview
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEpithelial–mesenchymal transitionTransition (genetics)Mesenchymal stem cellComputational biologyCell biologyChemistryComputer scienceBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

Epithelial–mesenchymal transition (EMT) encompasses dynamic changes in cellular organization from epithelial to mesenchymal phenotypes, which leads to functional changes in cell migration and invasion. EMT occurs in a diverse range of physiological and pathological conditions and is driven by a conserved set of inducing signals, transcriptional regulators and downstream effectors. With over 5,700 publications indexed by Web of Science in 2019 alone, research on EMTis expanding rapidly. This growing interest warrants the need for a consensus among researchers when referring to and undertaking research on EMT. This Consensus Statement, mediated by‘the EMT International Association’ (TEMTIA), is the outcome of a 2-year-long discussion among EMT researchers and aims to both clarify the nomenclature and provide definitions and guidelines for EMT research in future publications. We trust that these guidelines will help to reduce misunderstanding and misinterpretation of research data generated in various experimental models and to promote cross-disciplinary collaboration to identify and address key open questions in this research field. While recognizing the importance of maintaining diversity in experimental approaches and conceptual frameworks, we emphasize that lasting contributions of EMT research to increasing our understanding of developmental processes and combatting cancer and other diseases depend on the adoption of a unified terminology to describe EMT.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.331
GPT teacher head0.511
Teacher spread0.180 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2021
Admission routes1
Has abstractyes

Explore more

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