Developments in the field of allergy in 2008 through the eyes of<i>Clinical & Experimental Allergy</i>
Bibliographic record
Abstract
In 2008, many thousands of articles were published on the subject of allergic disease with over 200 reviews, editorials and original papers in Clinical & Experimental Allergy alone. These represent a considerable amount of data and even the most avid reader could only hope to assimilate a small fraction of this knowledge. There is therefore a pressing need for the key messages that emerge from a journal such as Clinical & Experimental Allergy to be summarized by experts in the field in a form that highlights the significance of the developments and sets them in the context of important findings in the field published in other journals. This also has the advantage of making connections between new data in conditions such as asthma, where articles often appear in different sections of the journal. As can be seen from this review, the body of work is diverse both in terms of the disease of interest and the discipline that has been used to investigate it. However, taken as a whole, we hope that the reader will gain a flavour of where the field is mature, where there remain controversies and where the cutting edge is leading.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".