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Record W2111725607 · doi:10.1079/pavsnnr20083080

Impacts of avian influenza virus on animal production in developing countries.

2009· article· en· W2111725607 on OpenAlex

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

VenueCABI Reviews · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversité de Montréal
FundersDepartment for International Development
KeywordsInfluenza A virus subtype H5N1LivestockComparabilityDeveloping countryDistribution (mathematics)Economic impact analysisBusinessProduction (economics)Highly pathogenicControl (management)Natural resource economicsEconomicsPublic economicsEconomic growthBiologyMicroeconomicsEcology

Abstract

fetched live from OpenAlex

Abstract This paper reviews the (predominantly grey) literature on impacts of highly pathogenic avian influenza (HPAI) strain H5N1 and control responses on the livestock sector and associated industries in developing countries. The authors distinguish between impacts that arise directly through HPAI-related morbidity and mortality, those that are a consequence of public intervention to control or eradicate HPAI, and impacts that are mediated through market reactions. The paper further considers how these impacts propagate up- and downstream through related supply and distribution networks, how short-term reactions are followed by longer-term adjustments, how impacts include direct cost elements and foregone income, and why losses to the poultry sector will, at least to some extent, be 'passed on' on the one hand, for example through compensation, and, on the other hand, be compensated for by gains in other livestock subsectors. Differences in methodology applied in the reviewed reports result in a lack of comparability of estimates for HPAI 'costs/impacts' across countries and even within countries and are compounded by information deficits. Despite these shortcomings, the literature permits some significant conclusions to be drawn on the relative importance of direct and indirect impacts and on their distribution across different types of poultry producers. The paper ends by outlining directions of future research that combine epidemiology and economics to provide a framework for disease control decision-making.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.082
GPT teacher head0.318
Teacher spread0.236 · 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