Bibliographic record
Abstract
As of November 2009, the ongoing Influenza A H1N1 pandemic appears to be relatively mild compared to scenarios that were foreseen or feared in many pandemic preparedness plans. Currently, most H1N1 influenza patients do not experience serious complications and they recover even without treatment with antiviral drugs. Serious complications are most commonly seen among the existing risk groups for seasonal influenza, e.g., patients with pre-existing chronic respiratory diseases. However, morbidity and mortality rates among children and young adults with no previous medical history are relatively high compared to seasonal influenza. It is still uncertain how the pandemic will develop in the coming months, but one can expect that the pandemic vaccines that have become available since the beginning of November 2009 will most likely make the pandemic ‘manageable’—at least in developed countries. A number of countries like Australia, Canada and the Netherlands expect to have sufficient vaccines to immunise the whole population. However, people in other parts of the world, especially in low-income countries, may have no access to vaccination at all, despite the fact that due to socio-economic deprivation and limited access to health care, they are much more vulnerable to significant negative effects from the disease. Once again, this pandemic underlines the enormous inequities in health and in access to health care between countries.
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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
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".