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Record W2793888838 · doi:10.1007/s11914-018-0423-2

The Role of the Immune Cells in Fracture Healing

2018· review· en· W2793888838 on OpenAlexaff
Gurpreet S. Baht, Linda Vi, Benjamin A. Alman

Bibliographic record

VenueCurrent Osteoporosis Reports · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of Toronto
FundersNational Institute on Aging
KeywordsBone healingOsteoimmunologyImmune systemMesenchymal stem cellBone marrowMedicineImmunologyCell biologyHaematopoiesisBone fractureBiologyStem cellAnatomyInternal medicineReceptor

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Bone fracture healing is a complex physiological process relying on numerous cell types and signals. Inflammatory factors secreted by immune cells help to control recruitment, proliferation, differentiation, and activation of hematopoietic and mesenchymal cells. Within this review we will discuss the functional role of immune cells as it pertains to bone fracture healing. In doing so, we will outline the cytokines secreted and their effects within the healing fracture callus. RECENT FINDINGS: Macrophages have been found to play an important role in fracture healing. These immune cells signal to other cells of the fracture callus, modulating bone healing. Cytokines and cellular signals within fracture healing continue to be studied. The findings from this work have helped to reinforce the importance of osteoimmunity in bone fracture healing. Owing to these efforts, immunomodulation is emerging as a potential therapeutic target to improve bone fracture healing.

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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

Citations272
Published2018
Admission routes1
Has abstractyes

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