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Record W2908121688 · doi:10.21037/jtd.2018.12.84

Country activities of Global Alliance against Chronic Respiratory Diseases (GARD): focus presentations at the 11th GARD General Meeting, Brussels

2018· article· en· W2908121688 on OpenAlexaff
Jean Bousquet, Yousser Mohammad, Anna Bedbrook, Teresa To, Rachel McGihon, Cristina Bárbara, E. Melo-Gomes, José Rosado‐Pinto, Paula Simão, Francisco George, Antonello Punturieri, James P. Kiley, Elizabete Nunes, Anilsa Cossa, Paulo Augusto Moreira Camargos, Raphael Stelmach, Álvaro A. Cruz, Marylin Valentin Rostan, Anahí Yáñez, Sandra Nora González Díaz, Marilyn Urrutia‐Pereira, Moisés A. Calderón, René Maximiliano Gómez, Zachary M. German, Vı́tězslav Kolek, V Špičák, Le Thi Tuyet Lan, Suzanne S. Hurd, Claude Lenfant, Arzu Yorgancıoğlu, Bilun Gemicioğlu, Banu Ekinci, Zubeyda Ozkan, Bassam Abou- Alzahab, Ahmad Dmeirieh, Rania Shifa, Hazar Faroun, Aicha AlJaber, Ramsa Halloum, Yassine Fatmeh, Ammar Alzein, Jamal Aloush, Ghazal Dib, Rafea Shaaban, Margarete Arrais, Maria Do Céu Teixeira, Cláudia Conceição, Paulo Ferrinho

Bibliographic record

VenueJournal of Thoracic Disease · 2018
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineAllianceFocus (optics)Respiratory systemIntensive care medicineInternal medicineGeography

Abstract

fetched live from OpenAlex

The Global Alliance against Chronic Respiratory Diseases (GARD) is a voluntary network of national and international organizations, institutions and agencies led by the World Health Organization (WHO), working towards the vision of a world where all people breathe freely (1). GARD is supporting WHO in successfully implementing the WHO’s Global Action Plan for the Prevention and Control of Noncommunicable Diseases (NCDs) 2013–2020. The GARD report on GARD activities is published on a regular basis. Collaboration among GARD countries is critical for sharing experiences and providing technical assistance to developing countries based on each country’s needs (2). The annual GARD meeting is a unique opportunity for assembling all of the GARD participants from developed and developing countries: European countries, North and South American Countries, China, Vietnam as well as Eastern Mediterranean, and African countries. Coordinator for Management of NCDs in the WHO Department for Management of Noncommunicable Diseases, Disability, Violence and Injury Prevention (Cherian Varghese) is present at this meeting. The annual meeting of GARD is a forum for exchanging opinions in order to improve care for chronic respiratory diseases (CRDs) and to achieve the GARD goal—a world where all people breathe freely. Experts—in collaboration with WHO—are helping developing countries to achieve their projects regarding teaching, research and programming for CRD. Each year, there is a poster presentation session on country activities. Each participant is able to present his/her country activities that have been achieved since the last meeting. This is followed by discussion. In this paper, we summarize the posters presented during the 11th GARD general meeting. We hope that this will give readers of the GARD section an opportunity to learn for their countries. We can find all posters on the link: https://gard-breathefreely.org/resources-poster/.

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)0.002
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0940.015

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 head0.016
GPT teacher head0.342
Teacher spread0.326 · 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
GenreOther

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

Citations21
Published2018
Admission routes1
Has abstractyes

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