DIVERSITY OF HEPATITIS C VIRUS
Bibliographic record
Abstract
Objective: (1)To understand the diversity in HCV glycoprotein E1 and E2sequences at different stages of infection. (2) Method widely used in evolutionary studies of HIV,as a new gold standard in HCV research.Setting: Department of Biochemistry Sir Syed Institutest of Medical Sciences Karachi. Period. 1 Jan 2012 to 31 Dec 2012. Design: Experimentalanalysis. Methods: The samples derived from a xenomouse model of transmission and severalsamples from naturally occurring transmission as well as sequences from acute stage ofinfection. we utilized single genome amplification (SGA) technique to recover full- length E1sequences. SGA of full-length E1 glycoprotein sequences, followed by direct sequencingminimizes in vitro generated artifacts and experimental biases associated with the standard bulkamplification and cloning approach, giving an accurate representation of investigated intrahostpopulation. Analysis and results: Comparative analyses of sequences derived from threedifferent settings were performed, in conjunction with a range of phylogenetic tests. As full-lengthE1 sequences were utilised. Conclusions: The role of glycoprotein E1 and E2 during theinfection of HCV was Known. The new gold standard in HCV research prove to be of greatimportance.
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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 | 0.000 | 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) | 0.002 | 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".