Anaphylaxis to a blood feeding leech
Bibliographic record
Abstract
Title Page:Article Type: Letter to the EditorTitle: Anaphylaxis to a blood feeding leechAuthors: Carmen H. Li MSc1,2*, Maggie Jiang MD3*, Gabriele Gadermaier PhD4, Sebastian Kvist PhD5,6,7 Julia E. M. Upton MD8,9, Xiaojun Yin PhD1, Jennifer A. Hoang MSc MDS1,10, Mikhail Monteiro BSc1, Lisa Hung PhD1,10, Akash Kothari MSc1,2, Theo J. Moraes MD PhD1,9, Peter Vadas MD PhD3,10**, Thomas Eiwegger MD1,10,11,12***Co-first author**Co-senior author(1) Translational Medicine Program, Research Institute, Hospital for Sick Children, Toronto, ON, Canada(2) Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada(3) Division of Clinical Immunology and Allergy, St. Michael’s Hospital(4) Department of Biosciences and Medical Biology, Paris Lodron University Salzburg, Salzburg, Austria(5) Department of Ecology and Evolutionary Biology, University of Toronto, ON, Canada(6) Department of Invertebrate Zoology, Royal Ontario Museum, Toronto, ON, Canada(7) Swedish Museum of Natural History, Stockholm, Sweden(8) Division of Immunology and Allergy, Food Allergy and Anaphylaxis Program, The Hospital for Sick Children(9) Department of Pediatrics, University of Toronto, Toronto, ON, Canada(10) Department of Immunology, Temerty Faculty of Medicine, University of Toronto, Ontario, Toronto, Canada(11) Karl Landsteiner University of Health Sciences, Krems, Austria(12) Department of Pediatric and Adolescent Medicine, University Hospital St. Pölten, St. Pölten, AustriaCorrespondence: Thomas Eiwegger, MDChair, Department of Pediatric and Adolescent MedicineUniversity Hospital St. PöltenDunant-Platz 1, 3100 St. Pölten, AustriaEmail: thomas.eiwegger@stpoelten.lknoe.atTel.: +43 2742-9004-11740
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".