Bibliographic record
Abstract
Pediatric Allergy and Immunology (PAI) is joined in celebrating its 25th year by a scientific community of pediatric allergists/immunologists that has become global over the years. With this issue our journal can look back on a quarter of a century filled with remarkable development: 25 yr ago a few pioneers gathered as a working group, which was the basis of the European Society for Paediatric Allergy and Immunology (ESPACI). A few enthusiastic researchers from the United States, Japan, Australia, and other Asia–Pacific countries joined in to form a new platform, which was intended to facilitate communication about innovative research in our area of interest, to induce lively discussions, allow critical evaluation of controversial issues, and to announce the progress made in diagnosis and treatment of allergic and immune-mediated diseases, as well as provide novel ideas for the prevention and early intervention of allergies including asthma 1-15. At that time, allergology all over the world was considered to be a relatively new and consequently still weak discipline of clinical science. Therefore, not everyone shared the enthusiasm of pediatricians who thought that there were specific issues to address which would justify a subspecialty of allergology for pediatricians and a journal with a strong pediatric profile. The two editors in chief, Professor Bengt Björkstén from Linköping, Sweden and later Professor John Warner from London, UK, provided the basis of a successful development together with many key scientists from all over the world. Their professional expertise as well as their strong commitment turned out to be crucial for the remarkable success of the journal over the decades. Today it seems appropriate for me to ask some of the outstanding researchers, including the two past chief editors of our journal, to update the state of the art, express their opinions about our specialty and its current standing as well as give some advice for novel directions of research for the future 17-25. It appears that the scientific impact—the visibility as well as the global distribution of our journal—has developed in a really remarkable way, and many clinicians and scientists who have contributed a lot of effort and time over the years as reviewers, members of the editorial group or professionals working in the editorial office deserve credit for it. A special thanks goes to the Paediatric Section of the European Academy of Allergy and Clinical Immunology (EAACI) as well as the junior members of our academy who became strong partners and supporters of our journal 16. For me, it is a great privilege to serve together with my editorial team in Berlin to make our journal even stronger in the future as the common platform of communication between clinicians and researchers, ensuring the very best for our patients.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.035 | 0.031 |
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".