Complete genomic sequences for hepatitis C virus subtypes 4b, 4c, 4d, 4g, 4k, 4l, 4m, 4n, 4o, 4p, 4q, 4r and 4t
Bibliographic record
Abstract
In this study, we characterized the full-length genomic sequences of 13 distinct hepatitis C virus (HCV) genotype 4 isolates/subtypes: QC264/4b, QC381/4c, QC382/4d, QC193/4g, QC383/4k, QC274/4l, QC249/4m, QC97/4n, QC93/4o, QC139/4p, QC262/4q, QC384/4r and QC155/4t. These were amplified, using RT-PCR, from the sera of patients now residing in Canada, 11 of which were African immigrants. The resulting genomes varied between 9421 and 9475 nt in length and each contains a single ORF of 9018-9069 nt. The sequences showed nucleotide similarities of 77.3-84.3 % in comparison with subtypes 4a (GenBank accession no. Y11604) and 4f (EF589160) and 70.6-72.8 % in comparison with genotype 1 (M62321/1a, M58335/1b, D14853/1c, and 1?/AJ851228) reference sequences. These similarities were often higher than those currently defined by HCV classification criteria for subtype (75.0-80.0 %) and genotype (67.0-70.0 %) division, respectively. Further analyses of the complete and partial E1 and partial NS5B sequences confirmed these 13 'provisionally assigned subtypes'.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".