The emerging Haemophilus influenzae serotype a infection and a potential vaccine: Implementation science in action
Bibliographic record
Abstract
Haemophilus influenzae serotype b (Hib) was a major cause of meningitis in children until Hib conjugate vaccine was introduced into the routine infant immunization program and Hib disease in children was almost eliminated.In Alaska, northern Canada and other countries with Indigenous peoples, H. influenzae serotype a (Hia) has emerged as a significant cause of pneumonia, meningitis and septic arthritis especially in children under 24 months of age.A joint government initiative between the Public Health Agency of Canada (PHAC) and the National Research Council of Canada (NRC) was carried out to assess whether an Hia vaccine could be developed for the common good.The initiative included strategic partnerships with clinician researchers in Thunder Bay, Ontario who provide health services to Indigenous people and the Artic Investigations Program (AIP) of the United States Centers for Disease Control and Prevention (CDC) in Alaska.This government initiated and funded research identified that the development of an Hia vaccine is possible and ongoing surveillance that includes strain characterization is essential to understand the potential spread of Hia in North America and around the world.
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 | 0.027 | 0.079 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.040 | 0.039 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".