Correction to A thermo‐resistant and RNase‐sensitive cargo from <i>Giardia duodenalis</i> extracellular vesicles modifies the behaviour of enterobacteria
Bibliographic record
Abstract
Siddiq, A., Dong, G., Balan, B., Harrison, L. G., Jex, A., Olivier, M., Allain, T., & Buret, A. G. (2023). A thermo-resistant and RNase-sensitive cargo from Giardia duodenalis extracellular vesicles modifies the behaviour of enterobacteria. Journal of Extracellular Biology, 2, e109. https://doi.org/10.1002/jex2.109 In the originally-published article, incorrect text was included for the Acknowledgements and Conflict of Interest Statement sections. The correct text appears below. The article has been updated online. We apologize for this error. AB was funded by the Natural Science and Engineering Research Council of Canada (Grant RT690446). MO Research is supported by grants from the Canadian Institute for Health Research (Grant #159765) and the Natural Science and Engineering Research Council of Canada (Grant RGPIN/03863-2017). AR Jex was funded by the Australian National Health and Medical Research Foundation Leadership Fellowship program (APP1194330), Victorian State Government Operational Infrastructure Support, Australia and the Australian Government National Health and Medical Research Council Independent Research Institute Infrastructure Support Scheme. All co-authors have seen and agree with the contents of the manuscript and there is no conflict of interest
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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 | 0.002 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.084 | 0.043 |
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".