Serological and molecular markers for Hepatitis B virus in university students
Bibliographic record
Abstract
Introduction: Reports from the World Health Organization (WHO) show that the prevalence of hepatitis B virus (HBV) infections varies by geographical region and risk group. Purpose: The purpose of this study was to determine the prevalence of HBV infections, as well as the vaccination status, among university students from Bucaramanga. Methodology: This was a cross sectional study conducted in 2010 which included 1298 students from five universities. Serological markers for HBV infection were detected using ELISA. Viral genomes were detected with nested polymerase chain reaction (PCR). Results: Active infections were established in 0.15% of the study population, and this finding was confirmed by PCR. Resolved infections were identified in 0.60% of the population. Isolated anti-HBc antibodies were found, 30.2% of vaccinated individuals. 67.9% of the study population was susceptible. No occult HBV was detected. Conclusions: The low prevalence of HBV infections reported in this study contrasts with the intermediate epidemiological pattern described in the region. We found poor vaccination coverage and absence of occult hepatitis B among these university students.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".