MétaCan
Menu
Back to cohort
Record W2588421265 · doi:10.21037/sci.2017.02.05

Schwann cells: an emerging player in tissue regeneration

2017· letter· en· W2588421265 on OpenAlexaff
Adam P. W. Johnston

Bibliographic record

VenueStem Cell Investigation · 2017
Typeletter
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsRegeneration (biology)BiologyAnatomyCell biology

Abstract

fetched live from OpenAlex

The neural crest is a transient developmental structure which gives rise to a host of diverse cellular lineages as well as bona fide multipotent stem that persist into late development (1) and potentially thereafter. One of these neural crest derivatives, Schwann cells, function primarily as physical and trophic support for nerve axons; however, recent work has highlighted their remarkable phenotypic and functional plasticity in a variety to cellular contexts (2). In this regard, our recent work (3) has contributed to the growing Schwann cell “resume” and provides further support for non-canonical functions of Schwann cells in tissue repair and homeostasis. Herein, I will further discuss commentary supplied by Kaucha and colleagues (4) and Montoro and colleagues (5) regarding our recent investigation of the role of de-differentiated Schwann cells, termed Schwann cell precursors (SCPs) in digit regeneration (3).

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)0.003
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0120.014
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 head0.075
GPT teacher head0.293
Teacher spread0.218 · 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
GenreCommentary

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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueStem Cell InvestigationSame topicNerve injury and regenerationFrench-language works237,207