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Record W4205428045 · doi:10.1126/sciimmunol.abf7777

Three tissue resident macrophage subsets coexist across organs with conserved origins and life cycles

2022· article· en· W4205428045 on OpenAlexafffund
Sarah A. Dick, Anthony Wong, Homaira Hamidzada, Sara Nejat, Robert Nechanitzky, Shabana Vohra, Brigitte Mueller, Rysa Zaman, Crystal Kantores, Laura Aronoff, Abdul Momen, Duygu Nechanitzky, Wanda Y. Li, Parameswaran Ramachandran, Sarah Q. Crome, Burkhard Becher, Myron I. Cybulsky, Filio Billia, Shaf Keshavjee, Seema Mital, Clinton S. Robbins, Tak W. Mak, Slava Epelman

Bibliographic record

VenueScience Immunology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsHospital for Sick ChildrenPrincess Margaret Cancer CentreSickKids FoundationUniversity Health NetworkUniversity of TorontoToronto General HospitalTed Rogers Centre for Heart Research
FundersCanadian Institutes of Health Research
KeywordsBiologyMacrophageYolk sacMonocyteCCR2PopulationFate mappingCompartment (ship)Cell biologyImmunologyGeneGeneticsInflammationEmbryonic stem cellEmbryoChemokine

Abstract

fetched live from OpenAlex

macrophages were the most transcriptionally conserved subset across mouse tissues and between mice and humans, despite organ- and species-specific transcriptional differences. Here, we define the existence of three murine macrophage subpopulations based on common life cycle properties and core gene signatures and provide a common starting point to understand tissue macrophage heterogeneity.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.015
GPT teacher head0.277
Teacher spread0.263 · 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
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

Citations512
Published2022
Admission routes2
Has abstractyes

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