Bibliographic record
Abstract
Northern America consists of two major industrialized nations, Canada and the United States, with populations of 38.7 million and over 336 million, respectively. The United Nations definition of the region includes Bermuda, Greenland, Saint Pierre and Miquelon. For this book, Greenland is included in the chapter on the Arctic and Antarctica, and Bermuda is included in the chapter on the Caribbean. Infectious agents in Northern America are typical of those identified in most developed countries, but some regionally specific pathogens exist. Agents and illnesses specific to Northern America (or less commonly recognized in other world regions) include Babesia, Ehrlichia, Anaplasma , Lyme, Rocky Mountain spotted fever, and Coccidioides . West Nile virus has been established in the region since its initial identification in 1999. Foodborne illnesses cause an estimated 48 million illnesses in the United States annually, with the majority attributed to infectious agents including Salmonella spp., norovirus, Shiga toxin-producing Escherichia coli, Campylobacter spp ., Clostridium perfringens , Giardia , and Cyclospora . Community-acquired Clostridium difficile infection is well-established, yet rates are not increasing as rapidly as they are for healthcare facility-associated infection. Antimicrobial resistance is a common concern when treating infections in Northern America, especially concerning multi-resistant Gram-negative bacilli.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.208 | 0.091 |
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".