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Record W4285082233 · doi:10.1016/j.xpro.2022.101534

A protocol to isolate bone marrow innate lymphoid cells for alymphoid mouse reconstitution

2022· article· en· W4285082233 on OpenAlexaff
Nicolas Jacquelot, Qiutong Huang, Gabrielle T. Belz, Cyril Seillet

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersDiamantina Institute, University of QueenslandCancer Council NSWNational Health and Medical Research CouncilState Government of VictoriaUniversity of QueenslandCancer AustraliaTranslational Research Institute AustraliaMultiple Sclerosis Australia
KeywordsInnate lymphoid cellInnate immune systemBiologyBone marrowAdoptive cell transferFunction (biology)Progenitor cellImmunologyTranscriptomeCell biologyAcquired immune systemStem cellImmune systemGeneT cellGene expressionGenetics

Abstract

fetched live from OpenAlex

Innate lymphoid cells (ILCs) and adaptive T cells remain a challenge to study because of a significant overlap in their transcriptomic profiles. Here, we describe the adoptive transfer of ILC progenitors into mice genetically deficient in innate and adaptive immune cells to allow detailed study of the development and function of ILCs and gene regulation in an in vivo setting. For complete details on the use and execution of this protocol, please refer to Jacquelot et al. (2021) and Seillet et al. (2016).

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0340.018

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 head0.290
Teacher spread0.262 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations1
Published2022
Admission routes1
Has abstractyes

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