Correction
Bibliographic record
Abstract
Vol 46 (1) 2016, DOI 10.1002/eji.201545628 Dendritic-cell expression of Ship1 regulates Th2 immunity to helminth infection in mice Matthew J. Gold, Frann Antignano, Michael R. Hughes, Colby Zaph and Kelly M. McNagny In the above mentioned article, the authors inadvertently omitted an acknowledgement. The complete correct Acknowledgements section is given here: We thank Rupi Dhesi and Les Rollins for core support, Andy Johnson and the UBCFlow facility, and Michael Williams and the UBC AbLab. This work was supported by the AllerGen Network Centre of Excellence (K.M.M. and M.J.G.) and Canadian Institute of Health Research (C.Z. and K.M.M., MOP-137142). M.J.G. was supported by an AllerGen CAIDATI training award, and F.A. is the recipient of a CIHR/Canadian Association of Gastroenterology/Crohn's and Colitis Foundation of Canada postdoctoral fellowship. We would like to take the opportunity to acknowledge Mr. Taka Murakami, Director of the BRC Genotyping service for animal genotyping and, especially, Ms. Ingrid Barta, of the BRC Histology Service, for providing excellent histological preparations including the one seen on the EJI Cover Issue from January 2016.
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 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 | 0.004 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.182 | 0.117 |
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".