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Record W4224244816 · doi:10.1016/j.xpro.2022.101280

An optimized protocol for phenotyping human granulocytes by mass cytometry

2022· article· en· W4224244816 on OpenAlexafffund
Nora Vivanco Gonzalez, John Paul Oliveria, Dmitry Tebaykin, Geoffrey T. Ivison, Kaori Mukai, Mindy Tsai, Luciene Borges, Kari C. Nadeau, Stephen J. Galli, Albert G. Tsai, Sean C. Bendall

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsMcMaster University
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institute on AgingNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsMass cytometryFlow cytometryGranulocyteImmunologyBiologyImmune systemCytometryCell biologyPhenotypeImmunoglobulin EAntibodyGeneticsGene

Abstract

fetched live from OpenAlex

Granulocytes encompass diverse roles, from fighting off pathogens to regulating inflammatory processes in allergies. These roles are represented by distinct cellular phenotypes that we captured with mass cytometry (CyTOF). Our protocol enables simultaneous evaluation of human basophils, eosinophils, and neutrophils under homeostasis and upon immune activation by anti-Immunoglobulin E (anti-IgE) or interleukin-3 (IL-3). Granulocyte integrity and detection of protein markers were optimized so that rare granulocyte populations could be deeply characterized by single cell mass cytometry. For complete details on the use and execution of this protocol, please refer to Vivanco Gonzalez et al. (2020).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0200.020

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 head0.034
GPT teacher head0.354
Teacher spread0.319 · 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
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

Citations2
Published2022
Admission routes2
Has abstractyes

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