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6th International Conference on Emerging Zoonoses

2012· article· en· W1498589954 on OpenAlexfundno aff
Robert E. Kahn, Igor Morozov, Heinz Feldmann, Jüergen A. Richt

Bibliographic record

VenueZoonoses and Public Health · 2012
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsnot available
FundersNational Institute on AgingUniversity of CalgaryKansas Bioscience AuthorityU.S. Department of Homeland Security
KeywordsOne HealthZoonosisWildlifeZoonotic diseaseBiologyPublic healthDiseaseMedicineVirologyEcologyPathology

Abstract

fetched live from OpenAlex

The 6th International Conference on Emerging Zoonoses, held at Cancun, Mexico, 24-27 February 2011, offered 84 participants from 18 countries, a snapshot of current research in numerous zoonoses caused by viruses, bacteria or prions. Co-chaired by Professors Heinz Feldmann and Jürgen Richt, the conference explored 10 topics: (i) The ecology of emerging zoonotic diseases; (ii) The role of wildlife in emerging zoonoses; (iii) Cross-species transmission of zoonotic pathogens; (iv) Emerging and neglected influenza viruses; (v) Haemorrhagic fever viruses; (vi) Emerging bacterial diseases; (vii) Outbreak responses to zoonotic diseases; (viii) Food-borne zoonotic diseases; (ix) Prion diseases; and (x) Modelling and prediction of emergence of zoonoses. Human medicine, veterinary medicine and environmental challenges are viewed as a unity, which must be considered under the umbrella of 'One Health'. Several presentations attempted to integrate the insights gained from field data with mathematical models in the search for effective control measures of specific zoonoses. The overriding objective of the research presentations was to create, improve and use the tools essential to address the risk of contagions in a globalized society. In seeking to fulfil this objective, a three-step approach has often been applied: (i) use cultured cells, model and natural animal hosts and human clinical models to study infection; (ii) combine traditional histopathological and biochemical approaches with functional genomics, proteomics and computational biology; and (iii) obtain signatures of virulence and insights into mechanisms of host defense response, immune evasion and pathogenesis. This meeting review summarizes 39 of the conference presentations and mentions briefly the 16 articles in this Special Supplement, most of which were presented at the conference in earlier versions. The full affiliations of all presenters and many colleagues have been included to facilitate further inquiries from readers.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.998

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)0.0030.000

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 head0.107
GPT teacher head0.378
Teacher spread0.271 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations16
Published2012
Admission routes1
Has abstractyes

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