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EAACI Position Paper: Prevention of work-related respiratory allergies among pre-apprentices or apprentices and young workers

2011· article· en· W1855403568 on OpenAlexaff
Gianna Moscato, Gianni Pala, Marcel‐André Boillat, Ilenia Folletti, Roy Gerth van Wijk, D OlgiatiDes Gouttes, L. Perfetti, Santiago Quirce, Andrea Siracusa, Jolanta Walusiak‐Skorupa, Susan M. Tarlo

Bibliographic record

VenueAllergy · 2011
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsToronto Western HospitalUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsApprenticeshipMedicineWorkforceFamily medicineWork (physics)AllergyOccupational medicinePosition paperAbsenteeismEnvironmental healthOccupational exposurePsychologyImmunologyPolitical science

Abstract

fetched live from OpenAlex

To cite this article: Moscato G, Pala G, Boillat MA, Folletti I, Gerth van Wijk R, Olgiati-Des Gouttes D, Perfetti L, Quirce S, Siracusa A, Walusiak-Skorupa J, Tarlo SM. EAACI Position Paper: Prevention of work-related respiratory allergies among pre-apprentices or apprentices and young workers. Allergy 2011; 66: 1164–1173. Apprenticeship is a period of increased risk of developing work-related respiratory allergic diseases. There is a need for documents to provide appropriate professional advice to young adults aiming to reduce unsuitable job choices and prevent impairment from their careers. The present document is the result of a consensus reached by a panel of experts from European and non-European countries addressed to allergologists, pneumologists, occupational physicians, primary care physicians, and other specialists interested in this field, which aims to reduce work-related respiratory allergies (rhinoconjunctivitis and asthma) among allergic or nonallergic apprentices and other young adults entering the workforce. The main objective of the document is to issue consensus suggestions for good clinical practice based on existing scientific evidence and the expertise of a panel of physicians.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.264
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations68
Published2011
Admission routes1
Has abstractyes

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