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Record W4213101703 · doi:10.1016/j.cellbi.2006.07.001

Abstracts from the International Symposium on Frontiers in Life Sciences: Molecular Basis of Disease, Prevention and Treatment

2006· article· en· W4213101703 on OpenAlex
Paul K.S. Chan, Lei Chen, Wing Ming Ho, Dean E. Dluzen, Bin Liu, Janet Mcdermott, Gu Xiao, Wei Dong, Nathalie Wong, Wah Tak, Yang Bao, Yan Liu, Hui Wang, Yan Lu, Jun Jiao, Zhi Wang, Teng Yan, An-Na Sun, Xiao-Chen Pan, Yang Guan, Leilei Yang, Ming‐Rong Wang, Xiao Yang, Bo Bai, Hai Liu, Yu Liu, Jing Chen

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

VenueCell Biology International · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsMontreal Heart Institute
FundersGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsCitationLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Avian influenza H5N1 has been spreading around Asia and extending globally over the last 3 years. Its devastating effect on economy and human health is tremendous. The potential of emerging to pandemic is real and imminent. Influenza pandemic is a rare event occurred only thrice in the last century. Theoretically, it requires a cascade of events starting from the emergence of a super strain from nature, most probably the aquatic bird species, wide spread propagation among animal reservoir, repeated human exposures for adaptation and mutation, and finally gaining human-to-human transmission efficiency. How far have the current strains of H5N1 reached? How long and how likely can the virus complete the reminding steps? Avian influenza infection rarely occurs in humans because of the difference in receptor recognition for human and avian viruses. Even when avian viruses can successfully establish infection in humans, they are not necessary more severe. For instance, H9 causes mild respiratory tract illnesses, H7 mainly causes conjunctivitis. Why H5N1 infection in humans has a fatality of more than 50%? Obviously, H5N1 is not just a severe version of human influenza. It is characterized by hypercytokinaemia, haemophagocytic syndrome and multi-organ failure. These clinico-pathological consequences cannot be explained solely by the nave host immunity. What do we know about the pathogenesis of avian influenza? Human influenza viruses preferentially recognize host receptors with a 2,6-linked sialic acid, whereas avian viruses recognize 2,3-linked sialic acid. Recent data indicate that such receptor specificity, in addition to provide a barrier for cross-species infection, may also play a role in determining the pathogenesis and transmission. There are many subtypes (16 H, 9 N) of influenza viruses circulating in nature. Apart from H5N1, are there other subtypes that we should be aware of?

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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