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Record W2904548584 · doi:10.1126/sciimmunol.aat4579

Neutrophils: New insights and open questions

2018· review· en· W2904548584 on OpenAlexaff
Klaus Ley, Hal M. Hoffman, Paul Kubes, Marco A. Cassatella, Arturo Zychlinsky, Catherine C. Hedrick, Sergio Catz

Bibliographic record

VenueScience Immunology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Heart, Lung, and Blood InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteAssociazione Italiana per la Ricerca sul CancroMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsInnate immune systemBiologyImmune systemImmunologyAcquired immune system

Abstract

fetched live from OpenAlex

Neutrophils are the first line of defense against bacteria and fungi and help combat parasites and viruses. They are necessary for mammalian life, and their failure to recover after myeloablation is fatal. Neutrophils are short-lived, effective killing machines. Their life span is significantly extended under infectious and inflammatory conditions. Neutrophils take their cues directly from the infectious organism, from tissue macrophages and other elements of the immune system. Here, we review how neutrophils traffic to sites of infection or tissue injury, how they trap and kill bacteria, how they shape innate and adaptive immune responses, and the pathophysiology of monogenic neutrophil disorders.

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)0.002
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.003

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 head0.056
GPT teacher head0.345
Teacher spread0.288 · 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

Citations541
Published2018
Admission routes1
Has abstractyes

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