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Record W4392785337 · doi:10.3791/65887-v

JoVE Video Dataset

2024· article· pt· W4392785337 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsColumbia College
Fundersnot available
KeywordsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Engineered cell therapies utilizing chimeric antigen receptor (CAR)-T cells have achieved remarkable effectiveness in individuals with hematological malignancies and are presently undergoing development for the treatment of diverse solid tumors. So far, the preliminary evaluation of novel CAR-T cell products has predominantly taken place in xenograft tumor models using immunodeficient mice. This approach is chosen to facilitate the successful engraftment of human CAR-T cells in the experimental setting. However, syngeneic mouse models, in which tumors and CAR-T cells are derived from the same mouse strain, allow evaluation of new CAR technologies in the context of a functional immune system and comprehensive tumor microenvironment (TME). The protocol described here aims to streamline the process of mouse CAR-T cell generation by presenting standardized methods for retroviral transduction and ex vivo T cell culture. The methods described in this protocol can be applied to other CAR constructs beyond the ones used in this study to enable routine evaluation of new CAR technologies in immune-competent systems.

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)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.718
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.7180.452

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 head0.058
GPT teacher head0.393
Teacher spread0.334 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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