Bibliographic record
Abstract
Before the introduction of Haemophilus infl uenzae type b (Hib) conjugate vaccines, rates of invasive H. infl uenzae disease among indigenous people of the North American Arctic were among the highest in the world. Routine vaccination reduced rates to low levels; however, serotype replacement with non–type b strains may result in a reemergence of invasive disease in children. We reviewed population-based data on invasive H. infl uenzae in Alaska and northern Canada from 2000–2005; 138 cases were reported. Among 88 typeable isolates, 42 (48%) were H. infl uenzae type a (Hia); 35 (83%) occurred in indigenous peoples. Among Hia patients, median age was 1.1 years; 62 % were male; 1 adult died. Common clinical manifestations included meningitis, pneumonia, and septic arthritis. Overall annual incidence was 0.9 cases per 100,000 population. Incidence among indigenous children <2 years of age in Alaska and northern Canada was 21 and 102, respectively. Serotype a is now the most common H. infl uenzae serotype in the North American Arctic; the highest rates are among indigenous children. Haemophilus infl uenzae causes illnesses ranging from local respiratory infection to serious invasive disease, including meningitis, epiglottitis, septic arthritis, and septicemia (1). Among the encapsulated strains (a to f) that have been identified, H. infl uenzae serotype b (Hib) is the most virulent (1–4). Nonencapsulated (nontypeable) strains
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".