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Record W2149415552 · doi:10.1186/1710-1492-6-s4-a2

Knowledge translation opportunities in allergic disease and asthma

2010· article· en· W2149415552 on OpenAlexaffvenueabout
Diana Royce

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2010
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAsthmaExcellenceAllergyMedicineDiseaseFood allergyAllergen immunotherapyFamily medicineAllergenEnvironmental healthImmunologyPolitical science

Abstract

fetched live from OpenAlex

AllerGen NCE Inc., the Allergy, Genes and Environment Network, is a national, multi-disciplinary, multi-sectoral network for research and discovery, knowledge translation and capacity building. AllerGen is dedicated to improving the quality of life for allergy asthma and related immune disease sufferers by supporting research that leads to new diagnostic tests, better medications, more effective public policies and an increase in the number of medical professionals researching and practicing in this area. The Networks of Centres of Excellence (NCE) program, of which AllerGen is a part, is a strategic initiative aligned with Canada’s Science and Technology strategy. The NCE program aims to close the ‘development-to-delivery’ gap, and accelerate the rate at which research results contribute to new, evidence-based, cost-effective policies, products and services that generate social and economic benefits for Canadians. The burden of allergy, asthma and related immune disease is significant and growing world-wide, and while the underlying causes of these diseases are actively being studied, the origins of these diseases are still not well understood. According to the results of the International Study of Asthma and Allergies in Childhood (ISAAC) Study, Phase III (2003) results, 47% of Canadian children have suffered from allergic rhinitis; 39% have experienced wheezing; 22.4% have been diagnosed with asthma; and, 19% have experienced atopic eczema [1]. According to Health Canada, non-food allergies are now the most common chronic condition in Canadians 12 years of age and older [2]. The economic impact of these diseases in Canada is in excess of $15 billion annually, when one includes the cost of ambulatory care, in-patient stays, emergency department visits, physician and facility payments, prescribed medications and productivity losses at school, work and at home as a direct result of these diseases [3]. This annual cost is comparable to the economic impact of arthritis and other chronic conditions. Ontario data show that 14% of all asthma-related emergency department visits occur in children between birth and 4 years of age, and that 21% of asthma prevalent cases were children and adolescents up to 19 years of age [4]. However, hospital admissions for asthma have decreased for both children and adults since 1996, and asthma as a cause of death is relatively uncommon and decreasing among all age groups in the developed world. Globally, asthma is more prevalent among the developed countries and in major city centres [5]. Among the countries with somewhat lower prevalence rates, such as India and China, which represent 37% of the global population, recent research suggests that as these countries industrialize, allergy, asthma and related immune disease prevalence rates are rising rapidly, mirroring the experience of more developed countries. Given the Canadian Institutes of Health Research’s strategic vision to position Canada as a world leader in the creation and use of knowledge derived from health research that benefits Canadians and the global community, Canadian researchers and their international partners have a significant opportunity to work in collaborative networks to accelerate the translation of research into practice, and knowledge to action, to improve allergic disease and asthma awareness, education, management and control. A recent analysis by Teresa To, from The Hospital for Sick Children [6], reveals that for Ontarians, the lifetime risk of developing chronic asthma is 1 in 3 - the same as the risk of developing cancer and diabetes. However, unlike cancer and diabetes, the substantial lifetime risk of asthma begins at an early stage in life and persists throughout the life span, triggering heightened disease burden, potential productivity loss and other economic costs. Building upon the work done in 2004 by a team led by Rejean Landry, AllerGen developed a publicly available KT planning tool called Knowledge Translation Planning Tools for Allergic Disease Researchers. This tool provides a guide for researchers, their stakeholders and partners to collaboratively develop translational strategies and tactics that will help accelerate the rate of dissemination, uptake and application of allergy, asthma and related immune disease research to improve the quality of life for patients, facilitate optimal care by health providers and reduce the economic drag resulting from the burden of these diseases [7]. Working with national and international partners, such as the Karolinska Institute in Sweden, AllerGen is committed to facilitating efforts to improve allergic disease and asthma management and control, discover the root causes of these diseases and accelerate the application of research findings and KT activities for social and economic benefits nationally and globally.

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 imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.058
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0040.010
Scholarly communication0.0130.014
Open science0.0030.012
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0320.004

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 head0.066
GPT teacher head0.346
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2010
Admission routes3
Has abstractyes

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