Killer germs: microbes and diseases that threaten humanity
Bibliographic record
Abstract
Discover the unseen assassins that plague humanity. Until recently, most of us went about our daily lives with a false sense of public health security. Epidemics were a thing of the past, the AIDS crisis had diminished, and an annual vaccination kept the flu at bay. Then, in late 2001, all of those illusions of public health safety were suddenly shattered. A litany of terrifying images and events became all to familiar, from federal agents surreally swathed in biohazard suits to the daily evacuation of major government buildings for anthrax decontamination. The lethal power of microscopic organisms - no longer confined to the lab - permeated our collective psyches, forcing us to confront the serious threat posed by killer germs.This updated edition of Barry and David Zimmerman's classic on the subject offers a riveting retrospective of the havoc-wreaking microbes of the past as well as an engrossing exploration of emerging threats, including a new chapter on bioterrorism. In these pages, you'll discover: what makes smallpox the most potentially devastating of all bioweapons, and how prepared we are to fight it; why tuberculosis - already responsible for 2 billion deaths - is on the rise in the United States, Canada, and Europe; how antibiotic overload might one day turn a simple paper cut or skinned knee into a source of fatal infection; and why virologists fear that an easily transmissible, highly virulent superflu - strong enough to rival the strain that killed millions in 1918 - is imminent. From the bygone bubonic plague to the modern nightmare of Ebola, Killer Germs offers a fascinating examination of the horrors humanity has faced and the actions required to provide hope for the future.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".