MétaCan
Menu
← Back to cohort
Record W4407838464 · doi:10.1038/s41467-025-57187-w

Author Correction: Proteomic profiling identifies muscle-invasive bladder cancers with distinct biology and responses to platinum-based chemotherapy

2025· erratum· en· W4407838464 on OpenAlexaff
Alberto Contreras‐Sanz, Gian Luca Negri, Moritz J. Reike, Htoo Zarni Oo, Joshua Scurll, Sandra E. Spencer Miko, K. Nielsen, Kenichiro Ikeda, Gang Wang, Chelsea Jackson, Shilpa Gupta, Morgan E. Roberts, David M. Berman, Roland Seiler, Gregg B. Morin, Peter C. Black

Bibliographic record

VenueNature Communications · 2025
Typeerratum
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsCanada's Michael Smith Genome Sciences CentreQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsProfiling (computer programming)Computational biologyChemotherapyBiologyBioinformaticsCancer researchMedicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

In the version of the article initially published, the “Transcriptomic analysis and subtyping” section of the Methods included the sentence “The ERCC RNA control Spike-In Mix (Thermo Fisher) was added to the purified RNA prior to library construction to allow for data comparison across other gene expression experiments” which has now been removed as the ERCC RNA control spike-in mix was not added in this instance. This correction has been made to the HTML and PDF versions of the article.

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)0.005
metaresearch head score (Gemma)0.050
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 score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.050
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0360.030

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 head0.023
GPT teacher head0.349
Teacher spread0.325 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNature Communications→Same topicBladder and Urothelial Cancer Treatments→French-language works237,207→