Biodefense Principles and Pathogens Edited By M. S. Bronze and R. A. Greenfield Norfolk, United Kingdom: Horizon Bioscience, 2005. 838 pp. $380.00 (hardcover)
Bibliographic record
Abstract
This book, with 838 pages plus an introduction, provides a remarkable and comprehensive overview of a wide number of biodefense issues of potential interest to a variety of readers. The book is divided into 3 main parts: general issues in biopreparedness, diseases potentially resulting from deployment of agents or toxins, and specific issues pertaining to agroterrorism. The content of each of the 23 chapters can stand alone, with minimal overlap of information among chapters, and direct contact information for the senior author of each chapter is provided. Authors generally decoded various acronyms commonly used by molecular biologists, clinicians, and microbiologists, which should assist those not conversant in such specialized terminology. Readers who have already spent many weary hours searching for bioterrorism information on the usual Web sites or scouring journal articles will immediately be impressed by the scale and depth of the research shown. This book provides significantly more than the usual recitation of the Centers for Disease Control and Prevention categories A, B, and C lists, and it sparingly reiterates information otherwise provided at the Centers for Disease Control and Prevention Web site (http://www.bt.cdc.gov).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.050 |
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".