P69 Functionality, reliability, and performance of an accessorized pre-filled syringe with home-administered subcutaneous benralizumab for adult patients with severe asthma
Bibliographic record
Abstract
AH Mansur: Received speaker fees and payment (including gifts or other consideration or ‘in kind’ compensation) through attending advisory board meeting to various companies including Novatis, Roche, AstraZeneca, NAPP, BI; Received educational grants for service development from Novartis pharmaceuticals; Participated in Phase IIb and III clinical trials with AstraZeneca, Novartis, Roche GT Ferguson: Received consultancy fees from AstraZeneca, Boehringer Ingelheim, and Pearl Therapeutics; Served on board or advisory committee for AstraZeneca, Pearl Therapeutics, and Novartis; Received research support from AstraZeneca, Boehringer Ingelheim, Pearl Therapeutics, Sunovion, Novartis, and Theravance JS Jacobs: Speaker/Teacher for Shire, Teva; Clinical Investigator for CSL Behring, Genentech, Regeneron, Sanofi, Shire, and Teva; Acted on Advisory committee for CSL Behring, Pharming Group, and Regeneron; Served as Independent Contractor for Genentech, CSL Behring, Regeneron, and Teva J Hebert: Consultant: Novartis, Merck, Teva, CSL Behring, Baxter, Shire; Conference Speaker: Merck, Novartis, Shire, Meda, CSL Behring; Investigator in clinical trials: Merck, Novartis, Stallergenis, GSK, Boehringer Ingelheim, CSL Behring, DBV C Clawson: Employee of MedImmune; Holds stock in AstraZeneca W Tao: Employee of AstraZeneca Y Wu: Employee of AstraZeneca M Goldman: Employee of AstraZeneca
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".