Bibliographic record
Abstract
First available in Alaska in 1991, Haemophilus influenzae type b (Hib) conjugate vaccine has resulted in one of the greatest public health successes of the last 25 years. Prior to vaccine availability, Hib was the most common cause of meningitis in children, and Alaska Native children aged <5 years experienced rates of Hib disease that were 6-fold higher than similarly aged children in the United States (400–700 vs. 60–100 cases per 100,000 persons, respectively).1 The highest reported rate of Hib disease occurred in children from the Yukon-Kuskokwim (YK) Delta and Kotzebue, where 2–4 % of infants experienced Hib disease in the first year of life.1 Since routine vaccination was instituted, Hib disease rates in Alaska children have decreased by more than 95%. However, an analysis of Hib incidence from 2000–2006 revealed that Alaska Natives continue to experience substantially higher rates of Hib diseases compared to non-Native Alaskans (6.0 and 0.4 cases per 100,000 persons, respectively; Figure).2 Since 2002, 11 of 14 (79%) Hib cases in children aged <10 years occurred in the YK
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.315 | 0.107 |
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".