Bibliographic record
Abstract
Background: The International Health Regulations (IHR) 2005 calls for strengthening core capacities of the 194 World Health Organization (WHO) member countries. No single country has the resources to control spread of infectious diseases, and cross border collaborations and information sharing are important for early mitigation of a public health event of international concern (PHEIC). Given the disparity among countries, especially in the laboratory capabilities in many less developed countries (LDC) for the detection, risk assessment of, and response to public health events, one way to improve capacity is to tap into the vibrant communities of laboratory networks. To connect the expertise and to map global laboratory resources, WHO has launched the Global Laboratory Directory (GLaD). GLaD is conceived as a support system to encourage laboratory networks to be part of a global community of peers. It is to connect laboratory networks to leverage capabilities and capacities in support of effective preparedness in compliance with the IHR. GLaD comprises of three components: GLaDMap, GLaDNet and GLaDResource Methods: This abstract focuses on the GLaDMap component which is based on a combination of the “yellow pages” directory concept with the links of a social “facebook” community. It is a list of networks and their member laboratories using a web based interactive mapping technology. Laboratory networks upload information through a detailed questionnaire and their specifics are uploaded and displayed dynamically, highlighting their specialties, geographic location, partnerships and activities. Results: A dynamic display of laboratories and their connections will be demonstrated: A series of mapping exercise scenarios will highlight how peer communities are utilizing the mapping tool, focusing on networks for cholera, food safety, influenza and biosafety. Conclusion: GLaD is positioned to strengthen the WHO's capability to perform fully and effectively the functions entrusted to it under the IHR, in particular to link more isolated laboratories in LDCs with others for better global connectivity and readiness to mitigate PHEICs. Abstracts for SupplementInternational Journal of Infectious DiseasesVol. 14Preview Full-Text PDF Open Archive
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.114 | 0.049 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".