MétaCan
Menu
Back to cohort
Record W4411429023 · doi:10.1007/s12035-025-05134-7

Correction: Microglial Responses to MSC-EVs Treatment in Animal and Cellular Models of Ischemic Stroke: a Systematic Review with Meta-analysis

2025· review· en· W4411429023 on OpenAlexaff
Luis Pedro Bernardi, Thomas Hugentobler Schlickmann, Giovanna Carello‐Collar, Marco Antônio De Bastiani, Eduardo R. Zimmer, Elizandra Braganhol, Francieli Rohden, Diogo O. Souza

Bibliographic record

VenueMolecular Neurobiology · 2025
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsStroke (engine)Meta-analysisIschemic strokeNeurologyMicrogliaMedicineNeurosciencePhysical medicine and rehabilitationBioinformaticsPsychologyImmunologyInternal medicineIschemiaBiologyInflammationEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.016
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.010
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0310.004

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 head0.068
GPT teacher head0.315
Teacher spread0.247 · 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 designMeta-analysis
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

Citations0
Published2025
Admission routes1
Has abstractno

Explore more

Same venueMolecular NeurobiologySame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207