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Record W4303685431 · doi:10.3390/cells11193158

Mesenchymal Stem/Stromal Cells as a Therapeutic Tool in Cell-Based Therapy and Regenerative Medicine: An Introduction Expertise to the Topical Collection

2022· editorial· en· W4303685431 on OpenAlexafffund
Makram Merimi, Hassan Fahmi, Joery De Kock, Charline Beguin, Arsène Burny, Guido Moll, Alessandro Poggi, Mehdi Najar

Bibliographic record

VenueCells · 2022
Typeeditorial
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchCentre National pour la Recherche Scientifique et TechniqueBerlin-Brandenburg School for Regenerative TherapiesBundesministerium für Bildung und ForschungEuropean CommissionFonds De La Recherche Scientifique - FNRSUniversité de MontréalDeutsche ForschungsgemeinschaftArthritis Society
KeywordsMesenchymal stem cellRegenerative medicineMedicineCell therapyStem-cell therapyStromal cellStem cellPathologyBiologyCell biology

Abstract

fetched live from OpenAlex

We are pleased to present this opening editorial, introducing our topical collection, "The New Era of Mesenchymal Stromal/Stem Cell Functional Application: State of the Art, Therapeutic Challenges and Future Directions" [...].

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)0.006
metaresearch head score (Gemma)0.012
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0020.001
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0120.009

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 head0.031
GPT teacher head0.321
Teacher spread0.290 · 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
GenreEditorial

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

Citations9
Published2022
Admission routes2
Has abstractyes

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