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Record W1547580090 · doi:10.1002/0471142735.im0325s106

Isolation and Characterization of Mouse Innate Lymphoid Cells

2014· review· en· W1547580090 on OpenAlexaff
Timotheus Y.F. Halim, Fumio Takei

Bibliographic record

VenueCurrent Protocols in Immunology · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsInnate lymphoid cellFlow cytometryCytokineBiologyImmunologyCellCell biologyInnate immune systemImmune systemBiochemistry

Abstract

fetched live from OpenAlex

Innate lymphoid cells (ILCs) are rare populations of cytokine-producing lymphocytes and are divided into three groups, namely ILC1, ILC2, and ILC3, based on the cytokines that they produce. They comprise less than 1% of lymphocytes in mucosal tissues and express no unique cell surface markers. Therefore, they can only be identified by combinations of multiple cell surface markers and further characterized by cytokine production in vitro. Thus, multicolor flow cytometry is the only reliable method to purify and characterize ILCs. Here we describe the methods for cell preparation, flow cytometric analysis, and purification of murine ILC2 and ILC3.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.004

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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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
GenreReview

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

Citations37
Published2014
Admission routes1
Has abstractyes

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