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Record W4401265865 · doi:10.1038/s41591-024-03138-9

Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells

2024· article· en· W4401265865 on OpenAlexafffund
Chirayu Chokshi, Muhammad Vaseem Shaikh, Benjamin Brakel, Martín A. Rossotti, David Tieu, William Maich, Alisha Anand, Shawn C. Chafe, Kui Zhai, Yujin Suk, Agata Kieliszek, Petar Miletic, Nicholas Mikolajewicz, David Y. Chen, Jamie McNicol, Katherine Chan, Amy H.Y. Tong, Laura Kuhlmann, Lina Liu, Zahra Alizada, Daniel Mobilio, Nazanin Tatari, Neil Savage, Nikoo Aghaei, Shan Grewal, Anish Puri, Minomi Subapanditha, Dillon McKenna, Vladimir Ignatchenko, Joseph M. Salamoun, Jacek M. Kwiecień, Peter Wipf, Elizabeth R. Sharlow, John Provias, Jian‐Qiang Lu, John S. Lazo, Thomas Kislinger, Yu Lu, Kevin R. Brown, Chitra Venugopal, Kevin A. Henry, Jason Moffat, Sheila K. Singh

Bibliographic record

VenueNature Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsJuravinski Cancer CentreUniversity of OttawaPrincess Margaret Cancer CentreMcMaster University Medical CentreHospital for Sick ChildrenUniversity Health NetworkUniversity of TorontoSickKids FoundationNational Research Council CanadaMcMaster University
FundersMitacsCanadian Institutes of Health ResearchTerry Fox Research InstituteNational Cancer InstituteGovernment of CanadaFoundation for the National Institutes of Health
KeywordsGlioblastomaNeuroscienceCancer researchComputational biologyComputer scienceBiology

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 score0.003
Threshold uncertainty score0.007

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 integrity0.0000.001
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 head0.010
GPT teacher head0.303
Teacher spread0.292 · 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

Citations43
Published2024
Admission routes2
Has abstractno

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