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Record W3086103973 · doi:10.1111/imm.13260

Implications of cellular metabolism for immune cell migration

2020· review· en· W3086103973 on OpenAlex
Hannah Guak, Connie M. Krawczyk

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImmunology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsMcGill University
Fundersnot available
KeywordsChemokineImmune systemBiologyChemokine receptorCell biologyCell metabolismReceptorCytoskeletonCell migrationCellImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Cell migration is an essential, energetically demanding process in immunity. Immune cells navigate the body via chemokines and other immune mediators, which are altered under inflammatory conditions of injury or infection. Several factors determine the migratory abilities of different types of immune cells in diverse contexts, including the precise co-ordination of cytoskeletal remodelling, the expression of specific chemokine receptors and integrins, and environmental conditions. In this review, we present an overview of recent advances in our understanding of the relationship of each of these factors with cellular metabolism, with a focus on the spatial organization of glycolysis and mitochondria, reciprocal regulation of chemokine receptors and the influence of environmental changes.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.282
Teacher spread0.257 · 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