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Record W4313906308 · doi:10.35493/medu.39.22

CARs on the road: Who gets a seat?

2021· article· en· W4313906308 on OpenAlexaffvenue
Katherine Taplin, Preetama Badyal

Bibliographic record

VenueThe Meducator · 2021
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsChimeric antigen receptorImmunotherapyMedicineCancer researchOncologyImmunologyImmune system

Abstract

fetched live from OpenAlex

Chimeric antigen receptor (CAR) T-cell therapy is a form of immunotherapy that has shown potential for inducing complete remission in relapsed/refractory hematopoietic cancers. Depending on the patient’s therapeutic needs, CAR T-cells may be constructed using different cytoplasmic and extracellular domains to alter their affinity, persistence, and proliferation. While the therapy holds promise, the conventional use of CAR T-cell therapy is limited by the occurrence of side effects, substantial rates of relapse, and manufacturing logistics. The objective of this review is to discuss the potential of CAR T-cell therapies, as well as patient characteristics which may influence its efficacy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.046
GPT teacher head0.347
Teacher spread0.300 · 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 designNot applicable
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
Published2021
Admission routes2
Has abstractyes

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