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Developments in the field of allergy in 2008 through the eyes of<i>Clinical &amp; Experimental Allergy</i>

2009· review· en· W2917532431 on OpenAlexaff
Catarina Almqvist, Peter Bradding, Jamila Chakir, Didier G. Ebo, Clive Grattan, Harsha H. Kariyawasam, Erkki Savilahti, Glenis Scadding, Stefan Vieths, Andrew J. Wardlaw, Judith A. Woodfolk

Bibliographic record

VenueClinical & Experimental Allergy · 2009
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsHôpital du Saint-SacrementCegep de Sainte Foy
Fundersnot available
KeywordsContext (archaeology)AllergySubject (documents)AsthmaMedicineField (mathematics)DiseaseFood allergyImmunologyComputer scienceHistoryPathologyLibrary science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.146
GPT teacher head0.504
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2009
Admission routes1
Has abstractyes

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