Marshalling Science for Global Health: A Bilateral Workshop
Notice bibliographique
Résumé
Huge health disparities exist across regional and national boundaries; yet we also live in an interconnected world where pathogens and outbreaks that are more common elsewhere or that begin on distance shores affect our own patients and populations. Recognizing outbreaks and improving the prevention and treatment of infectious diseases are essential for improving health globally, and there has been a tremendous increase over the last decade in interest in and resources for global health. Despite this progress, many advances in healthcare still do not get implemented in low- and middle-income countries in a timely fashion, and diseases that cause substantial burdens of illness in these regions are ignored by the larger research community. Because of this, the communities are highest risk for outbreaks usually are least capable of recognizing and containing them. To address these issues, we propose to hold a workshop to develop an integrated global health surveillance, research and education network that links Canadian and California investigators with colleagues in low- and middle-income countries. New information technologies mean that poor infrastructures and remote locations may no longer be barriers to building effective surveillance and educational programs, and we have the opportunity to address global health challenges in ways not previously possible. Marshalling experts from academia, industry and public health, we would map out the available technologies needed to build a global health network capable of assisting in the formation of multi-disciplinary teams to address global health challenges and facilitating the introduction of health advances in low- and middle-income settings. Other long-term goals include identifying tools needed to improve country-wide collection of health data in low- and middle-resource settings, establishing essentially real-time surveillance of emerging public health risks from primary health data and establishing multi-disciplinary global health training programs. Canada and California have large foreign-born populations, annually receive millions of travelers from around the world and have underserved communities living in remote settings. The workshop is an important step towards building our joint capacity to better serve and protect our populations, to tackle crucial health issues for individuals most burdened by diseases, and to build world-class global health training programs. This proposal also builds on important initiatives already underway in both countries. The applicants are senior investigators with extensive experience working internationally and expertise in basic, clinical and social sciences as well as informational technology, and are well-qualified to undertake this exciting, ambitious proposal to improve health locally and globally.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,043 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,006 |
| Communication savante | 0,016 | 0,012 |
| Science ouverte | 0,004 | 0,023 |
| Intégrité de la recherche | 0,018 | 0,027 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,033 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».