Epstein Barr virus genome in nasopharyngeal carcinomas from New Zealand
Bibliographic record
Abstract
BACKGROUND: The population in New Zealand is a heterogeneous mix of Caucasians (80%), Maori (9%), and Polynesians (10%). It is believed that the Polynesians are of Chinese descent and may harbor the same high incidence of nasopharyngeal carcinoma (NPC). In addition, it is not known whether the Epstein-Barr virus (EBV) is as closely associated with the development of NPC in Polynesians as it is in those of Chinese origin. METHODS: This study reexamines the associative correlation between EBV and NPC with two methods of genetic detection, polymerase chain reaction (PCR) and in-situ hybridization (ISH). In addition, geographic heterogeneity was analyzed to determine whether there are differences in the prevalence of EBV in NPCs among the ethnic mixed populations found in New Zealand. Nasopharyngeal biopsy specimens from 20 patients with NPC and 36 controls were obtained from Auckland. RESULTS: With PCR, EBNA-1, a genomic sequence of EBV in NPC samples was able to be detected with 76.5% sensitivity and 96.7% specificity. By use of ISH, EBV was detected in NPC tissue with 82.4% sensitivity and 100% specificity. CONCLUSION: There seems to be no geoanthropologic differences in terms of the association of EBV with NPC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".