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Record W4387675036 · doi:10.1002/jex2.115

Cell culture‐derived extracellular vesicles: Considerations for reporting cell culturing parameters

2023· article· en· W4387675036 on OpenAlexaff
Faezeh Shekari, Faisal J. Alibhai, Hossein Baharvand, Verena Börger, Stefania Bruno, Owen G. Davies, Bernd Giebel, Mario Gimona, Ghasem Hosseini Salekdeh, Lorena Martín‐Jaular, Suresh Mathivanan, Inge Nelissen, Esther N. M. Nolte‐‘t Hoen, Lorraine O’Driscoll, Francesca Perut, Stefano Pluchino, Gabriella Pòcsfalvi, Carlos Salomón, Carolina Soekmadji, Simon Staubach, Ana Cláudia Torrecilhas, Ganesh Vilas Shelke, Tobias Tertel, Dandan Zhu, Clotilde Théry, Kenneth W. Witwer, Rienk Nieuwland

Bibliographic record

VenueJournal of Extracellular Biology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity Health Network
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsExtracellular vesiclesExtracellular vesicleStandardizationExtracellularVesicleFunction (biology)CellCell biologyChecklistBiotechnologyBiologyBiochemical engineeringComputer scienceBiochemistryMicrovesiclesEngineeringMembrane

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.168
metaresearch head score (Gemma)0.215
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.832
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1680.215
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.005
Science and technology studies0.0040.004
Scholarly communication0.0080.005
Open science0.0060.006
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.006

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 head0.038
GPT teacher head0.298
Teacher spread0.260 · 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.

Study designTheoretical or conceptual
DomainReporting
GenreMethods

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

Citations73
Published2023
Admission routes1
Has abstractyes

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