Abstracts from the International Symposium on Frontiers in Life Sciences: Molecular Basis of Disease, Prevention and Treatment
Bibliographic record
Abstract
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 naïve 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?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.079 | 0.045 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".