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Record W3132116659 · doi:10.1038/s41392-021-00463-0

PD-L1 regulates genomic stability via interaction with cohesin-SA1 in the nucleus

2021· letter· en· W3132116659 on OpenAlexaff
Wen Zhang, Jiali Jin, Yanjin Wang, Lan Fang, Min Liu, Xinbo Wang, Lin Ding, Linjun Weng, Tianhua Zhou, Ping Wang

Bibliographic record

VenueSignal Transduction and Targeted Therapy · 2021
Typeletter
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCohesinNucleusBiologyCell biologyGeneticsDNA

Abstract

fetched live from OpenAlex

Programmed death ligand-1 (PD-L1) is a type 1 transmembrane protein and highly expressed in various cancers that binds to PD-1 on T cells, inhibits T cell activity and proliferation, facilitates cancer cells to escape T cell-mediated immune surveillance. Immunotherapies by PD-L1/PD-1 blockade have shown effectiveness against different cancer types and revolutionizes cancer treatment in the clinic. However, the response rate to anti-PD-L1/PD-1 antibody remains at about 15–30% as a single agent. 1 Thus, there is more to understand regarding the function of PD-L1 in cancer.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0020.002

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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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 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

Citations21
Published2021
Admission routes1
Has abstractno

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