H1N1-influenza as Lazarus: Genomic resurrection from the tomb of an unknown
Bibliographic record
Abstract
The 1918–1919 pandemic of H1N1 virus influenza was the greatest acute plague of the 20th century. Incurring over 20 million human fatalities, however, was not a good strategy for sustaining the evolutionary fitness of the virus, because it is no longer extant; whereas, say, measles and chickenpox remain with us with no evidence of remarkable genetic change, although this may become more evident if they were to face total or near eradication through vaccination programs. The folly of flu virulence remains our chagrin, because the threat always looms over us that this family of viruses, endemic in birds, again may generate human-lethal gene reassortments. We had valid scares about that contingency with the appearance of H5N1 variant flu in Hong Kong just 3 years ago. Influenza can be regarded as a zoonosis prevalent in birds, many of them world travelers, with occasional outbreaks in humans and other animals mainly rooted in nature's own experiments in genetic engineering. Special importance is attached to reassortments between bird- and human-adapted strains most likely to occur in habitats with close contact between birds, e.g., ducks, humans, and swine (as a mixing reservoir; ref. 1). For these reasons, high urgency attaches to efforts to resurrect genetic information about the singularities of H1N1–1918. The intact virus is nowhere to be found, but genomic fragments can still be detected sensitively and diagnosed. Exemplifying the latest technical advances in the use of DNA amplification, reverse-transcriptase–PCR (RT-PCR), Jeffery Taubenberger and his associates at the Armed Forces Institute of Pathology initiated the tour de force of recovering sequences of flu from paraffin-embedded pathological specimens preserved since 1918 in the AFIP collections (2). These sources then were augmented by samples from frozen remains of an Inuit woman who succumbed to the flu in 1918 and was buried in permafrost at Brevig …
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".