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Record W4405902466 · doi:10.1007/978-3-031-53793-6_14

Nipah Outbreak Investigation in Bangladesh, 2007: A Case Study of One Health Partnership and Intersectoral Coordination

2024· book-chapter· en· W4405902466 on OpenAlex
Mahmudur Rahman, Nadia Ali Rimi, Rebeca Sultana, Nusrat Homaira, Jonathan H. Epstein, Stephen P. Luby

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainable development goals series · 2024
Typebook-chapter
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsOutbreakGeneral partnershipEnvironmental healthGeographyBusinessMedicineVirology

Abstract

fetched live from OpenAlex

Abstract One Health is increasingly recognized for its value in addressing emerging infectious disease threats. In Bangladesh, the integration of One Health approaches into outbreak investigation and response can be traced back to the advent of outbreaks of Nipah and avian influenza viruses. Through accounts from epidemiological, anthropological, ecological, and animal health investigations, this chapter narrates a case study of partnership among the government, development partners, and research organizations in Nipah virus outbreak management. It depicts how persuadable, collaborative and problem-solving leadership, cooperative approaches, common goals and mutual support could result in strong partnerships among different individuals and organizations towards building a One Health platform to achieve common goals.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.293
Teacher spread0.257 · 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