International Consensus Statement on Allergy and Rhinology: Rhinosinusitis
Bibliographic record
Abstract
Contributing Authors Isam Alobid, MD, PhD 1 , Nithin D. Adappa, MD 2 , Henry P. Barham, MD 3 , Thiago Bezerra, MD 4 , Nadieska Caballero, MD 5 , Eugene G. Chang, MD 6 , Gaurav Chawdhary, MD 7 , Philip Chen, MD 8 , John P. Dahl, MD, PhD 9 , Anthony Del Signore, MD 10 , Carrie Flanagan, MD 11 , Daniel N. Frank, PhD 12 , Kai Fruth, MD, PhD 13 , Anne Getz, MD 14 , Samuel Greig, MD 15 , Elisa A. Illing, MD 16 , David W. Jang, MD 17 , Yong Gi Jung, MD 18 , Sammy Khalili, MD, MSc 19 , Cristobal Langdon, MD 20 , Kent Lam, MD 21 , Stella Lee, MD 22 , Seth Lieberman, MD 23 , Patricia Loftus, MD 24 , Luis Macias‐Valle, MD 25 , R. Peter Manes, MD 26 , Jill Mazza, MD 27 , Leandra Mfuna, MD 28 , David Morrissey, MD 29 , Sue Jean Mun, MD 30 , Jonathan B. Overdevest, MD, PhD 31 , Jayant M. Pinto, MD 32 , Jain Ravi, MD 33 , Douglas Reh, MD 34 , Peta L. Sacks, MD 35 , Michael H. Saste, MD 36 , John Schneider, MD, MA 37 , Ahmad R. Sedaghat, MD, PhD 38 , Zachary M. Soler, MD 39 , Neville Teo, MD 40 , Kota Wada, MD 41 , Kevin Welch, MD 42 , Troy D. Woodard, MD 43 , Alan Workman 44 , Yi Chen Zhao, MD 45 , David Zopf, MD 46 Contributing Author Affiliations 1 Universidad de Barcelona; 2 University of Pennsylvania; 3 Louisiana State University Health Sciences Center; 4 Universidade de São Paulo; 5 ENT Specialists of Illinois; 6 University of Arizona; 7 University of Oxford; 8 University of Texas; 9 University of Indiana; 10 Mount Sinai Beth Israel; 11 Emory University; 12 University of Colorado; 13 Wiesbaden, Germany; 14 University of Colorado; 15 University of Alberta; 16 University of Alabama at Birmingham; 17 Duke University; 18 Sungkyunkwan University; 19 University of Pennsylvania; 20 Universidad de Barcelona; 21 Northwestern University; 22 University of Pittsburgh; 23 New York University; 24 Emory University; 25 University of British Columbia; 26 Yale University School of Medicine; 27 Private Practice; 28 Department of Otolaryngology, Hôtel‐Dieu Hospital, Centre de Recherche du Centre Hospitalier de l'Université de Montréal; 29 University of Adelaide; 30 Pusan National University; 31 University of California, San Francisco; 32 University of Chicago; 33 University of Auckland; 34 Johns Hopkins University; 35 University of New South Wales, Australia; 36 Stanford University; 37 Washington University; 38 Harvard Medical School; 39 Medical University of South Carolina; 40 Singapore General Hospital; 41 Taho University; 42 Northwestern University; 43 Cleveland Clinic Foundation; 44 University of Pennsylvania; 45 University of Adelaide; 46 University of Michigan
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 | 0.030 | 0.065 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.012 | 0.016 |
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".