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Record W4395011321 · doi:10.1038/s41586-024-07393-1

Author Correction: Targeting SWI/SNF ATPases in enhancer-addicted prostate cancer

2024· erratum· en· W4395011321 on OpenAlex
Lanbo Xiao, Abhijit Parolia, Yuanyuan Qiao, Pushpinder Bawa, Sanjana Eyunni, Rahul Mannan, Sandra E. Carson, Yu Chang, Xiaoju Wang, Yuping Zhang, Josh N. Vo, Steven Kregel, Stephanie A. Simko, Andrew Delekta, Mustapha Jaber, Heng Zheng, Ingrid J. Apel, Lisa McMurry, Fengyun Su, Rui Wang, Sylvia Zelenka-Wang, Sanjita Sasmal, Leena Khare, Subhendu Mukherjee, Chandrasekhar Abbineni, Kiran Aithal, Mital S. Bhakta, Jay Ghurye, Xuhong Cao, Nora M. Navone, Alexey I. Nesvizhskii, Rohit Mehra, Ulka N. Vaishampayan, Marco Blanchette, Yuzhuo Wang, Susanta Samajdar, Murali Ramachandra, Arul M. Chinnaiyan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNature · 2024
Typeerratum
Languageen
FieldMedicine
TopicCancer Mechanisms and Therapy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProstate cancerEnhancerATPaseBiologyCancer researchComputational biologyCancerGeneticsGeneBiochemistryEnzymeTranscription factor

Abstract

fetched live from OpenAlex

In the version of this article initially published, there was an error in column B, row 1 in Supplementary Table 1, where the unit incorrectly appeared as IC 50 (μM) instead of IC 50 (nM). In addition, we noticed that there was an image duplication of Extended Data Fig. 10h, where the image of SMARCA4/BRG1 IHC staining of kidney tissue from the enzalutamide group was inadvertently duplicated from the vehicle group. The conclusions of the paper remain unaffected. Supplementary Table 1 and Extended Data Fig. 10h have been updated to reflect these revisions.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0040.014
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.312
Teacher spread0.304 · 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