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Record W4242756756 · doi:10.1126/science.335.6067.400

Pause on Avian Flu Transmission Research

2012· article· en· W4242756756 on OpenAlexaff
Ron A. M. Fouchier, A. Garcia-Sastre, Yoshi Kawaoka, William Barclay, N. M. Bouvier, Ian H. Brown, I. Capua, H. Chen, R. W. Compans, R. B. Couch, N. J. Cox, P. C. Doherty, R. O. Donis, H. Feldmann, Y. Guan, J. Katz, H. D. Klenk, G. Kobinger, Jinru Liu, X. Liu, A. Lowen, T. C. Mettenleiter, Albert D. M. E. Osterhaus, P. Palese, Malik Peiris, D. R. Perez, J. A. Richt, S. Schultz-Cherry, J. Steel, K. Subbarao, D. E. Swayne, T. Takimoto, M. Tashiro, J. K. Taubenberger, P. G. Thomas, R. A. Tripp, T. M. Tumpey, R. J. Webby, R. G. Webster

Bibliographic record

VenueScience · 2012
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsPandemicInfluenza A virus subtype H5N1Human mortality from H5N1Influenza pandemicTransmission (telecommunications)PreparednessVirologyPublic healthInfluenza A virusVirusBiologyCoronavirus disease 2019 (COVID-19)MedicineDiseaseInfectious disease (medical specialty)Political scienceComputer science

Abstract

fetched live from OpenAlex

The continuous threat of an influenza pandemic represents one of the biggest challenges in public health. Influenza pandemics are known to be caused by viruses that evolve from animal reservoirs, such as in birds and pigs, and can acquire genetic changes that increase their ability to transmit in humans. Pandemic preparedness plans have been implemented worldwide to mitigate the impact of influenza pandemics. A major obstacle in preventing influenza pandemics is that little is known regarding what makes an influenza virus transmissible in humans. As a consequence, the potential pandemic risk associated with the many different influenza viruses of animals cannot be assessed with any certainty.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0040.009
Open science0.0020.004
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0350.017

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 head0.351
GPT teacher head0.538
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations33
Published2012
Admission routes1
Has abstractyes

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