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Record W3015056143 · doi:10.1016/j.ebiom.2020.102741

Corrigendum to ‘Roles of alternative RNA splicing of the Bif-1 gene by SRRM4 during the development of treatment-induced neuroendocrine prostate cancer’. [EBioMedicine 31 (2018) 267–275>

2020· erratum· en· W3015056143 on OpenAlexaff
Yu Gan, Yinan Li, Zhi Long, Ahn R. Lee, Ning Xie, Jessica M. Lovnicki, Yuxin Tang, Xiang Chen, Jiaoti Huang, Xuesen Dong

Bibliographic record

VenueEBioMedicine · 2020
Typeerratum
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProstate cancerCancer researchGeneRNA splicingAlternative splicingCancerAdenocarcinomaMedicineTranscriptomeProstateRNABiologyGene expressionExonInternal medicineGenetics

Abstract

fetched live from OpenAlex

The authors wish to point out that:i)There is a typo in one of the labels of Fig. 2a. In Fig. 2a (top right), “IHC Positive (H score < 0.3)” should be replaced with “IHC Negative (H score < 0.3)”;ii) These errors do not change the scientific conclusions of the article in any way. Roles of Alternative RNA Splicing of the Bif-1 Gene by SRRM4 During the Development of Treatment-induced Neuroendocrine Prostate CancerTreatment-induced neuroendocrine prostate cancer (t-NEPC) is an aggressive subtype of prostate cancer (PCa) that becomes more prevalent when hormonal therapy, chemotherapy, or radiation therapy is applied to patients with metastatic prostate adenocarcinoma (AdPC). How AdPC cells survive these anti-cancer therapies and progress into t-NEPC remains unclear. By comparing the whole transcriptomes between AdPC and t-NEPC, we identified Bif-1, an apoptosis-associated gene, which undergoes alternative RNA splicing in t-NEPC. Full-Text PDF Open Access

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.314
Teacher spread0.277 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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