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Record W3215495397 · doi:10.1111/imr.13040

Imaging reveals novel innate immune responses in lung, liver, and beyond*

2021· review· en· W3215495397 on OpenAlexafffund
Arpan Sharma Neupane, Paul Kubes

Bibliographic record

VenueImmunological Reviews · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Innovates - Health SolutionsCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsImmune systemBiologyInnate immune systemIntravital microscopyImmunologyHomeostasisOrganismImmunityNeuroscienceCell biologyIn vivoGenetics

Abstract

fetched live from OpenAlex

Highly dynamic immune responses are generated toward pathogens or injuries, in vivo. Multiple immune cell types participate in various facets of the response which leads to a concerted effort in the removal and clearance of pathogens or injured tissue and a return to homeostasis. Intravital microscopy (IVM) has been extensively utilized to unravel the dynamics of immune responses, visualizing immune cell behavior in intact living tissues, within a living organism. For instance, the phenomenon of leukocyte recruitment cascade. Importantly, IVM has led to a deep appreciation that immune cell behavior and responses in individual organs are distinct, but also can influence one another. In this review, we discuss how IVM as a tool has been used to study the innate immune responses in various tissues during homeostasis, injury, and infection.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.068
GPT teacher head0.337
Teacher spread0.269 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

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