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Record W4288447807 · doi:10.1038/s41588-022-01134-8

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment

2022· article· en· W4288447807 on OpenAlexfundno aff
William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Payman Yadollahpour, Jason Reeves, Rahul Mohan, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Orr Ashenberg, Samouil L. Farhi, Denis Schapiro, Prajan Divakar, Eric Miller, Daniel R. Zollinger, George Eng, Jason M. Schenkel, Jennifer Su, Carina Shiau, Patrick Yu, William A. Freed-Pastor, Domenic Abbondanza, Arnav Mehta, Joshua Gould, Conner Lambden, Caroline Porter, Alexander M. Tsankov, Danielle Dionne, Julia Waldman, Michael S. Cuoco, Lan Nguyễn, Toni Delorey, Devan Phillips, Jaimie L. Barth, Marina Kem, Debora Ciprani, Jorge Roldán, Piotr Zelga, Vjola Jorgji, Jonathan Chen, Zackery A. Ely, Daniel Zhao, Kit Fuhrman, Robin Fropf, Joseph Beechem, Jay S. Loeffler, David P. Ryan, Colin D. Weekes, Cristina R. Ferrone, Motaz Qadan, Martin J. Aryee, Rakesh K. Jain, Donna Neuberg, Jennifer Y. Wo, Theodore S. Hong, Ramnik J. Xavier, Andrew J. Aguirre, Orit Rozenblatt–Rosen, Mari Mino–Kenudson, Carlos Fernández‐del Castillo, Andrew S. Liss, David T. Ting, Tyler Jacks, Aviv Regev

Bibliographic record

VenueNature Genetics · 2022
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
FundersMoonshot Research and Development ProgramNational Cancer InstituteStand Up To CancerUniversity of California, San FranciscoKlarman Cell Observatory, Broad InstituteNational Science FoundationDamon Runyon Cancer Research FoundationPancreatic Cancer Canada FoundationPrincess Margaret Cancer FoundationLudwig Institute for Cancer ResearchCanadian Cancer Society Research InstituteSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Institute of Diabetes and Digestive and Kidney DiseasesLustgarten FoundationConquer Cancer FoundationGovernment of OntarioHoward Hughes Medical Institute
KeywordsBiologyTranscriptomePancreatic cancerMulticellular organismCancer researchProgenitor cellGene expression profilingComputational biologyPhenotypeBioinformaticsCellCancerStem cellGeneticsGene expressionGene

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.304
Teacher spread0.283 · 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

Citations413
Published2022
Admission routes1
Has abstractno

Explore more

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