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Record W2536640519 · doi:10.1161/atvbaha.116.308198

Monocyte Conversion During Inflammation and Injury

2016· review· en· W2536640519 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesHeart and Stroke Foundation of Canada
KeywordsInflammationMonocyteImmunologyInnate immune systemBone marrowAcquired immune systemImmune systemImmunityBiologyMedicine

Abstract

fetched live from OpenAlex

Monocytes are circulating leukocytes important in both innate and adaptive immunity, primarily functioning in immune defense, inflammation, and tissue remodeling. There are 2 subsets of monocytes in mice (3 subsets in humans) that are mobilized from the bone marrow and recruited to sites of inflammation, where they carry out their respective functions in promoting inflammation or facilitating tissue repair. Our understanding of the fate of these monocyte subsets at the site of inflammation is constantly evolving. This brief review highlights the plasticity of monocyte subsets and their conversion during inflammation and injury.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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