Updating MISEV: Evolving the minimal requirements for studies of extracellular vesicles
Bibliographic record
Abstract
The minimal information for studies of extracellular vesicles (EVs, MISEV) is a field-consensus rigour initiative of the International Society for Extracellular Vesicles (ISEV). The last update to MISEV, MISEV2018, was informed by input from more than 400 scientists and made recommendations in the six broad topics of EV nomenclature, sample collection and pre-processing, EV separation and concentration, characterization, functional studies, and reporting requirements/exceptions. To gather opinions on MISEV and ideas for new updates, the ISEV Board of Directors canvassed previous MISEV authors and society members. Here, we share conclusions that are relevant to the ongoing evolution of the MISEV initiative and other ISEV rigour and standardization efforts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.108 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.016 | 0.028 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".