Integrating Laboratory and Epidemiological Techniques for Population‐Based Surveillance of HIV Strains and Drug Resistance in Canada
Bibliographic record
Abstract
H IV is among the most genetically variable of human pathogens.Two major factors contribute to this genetic diversity: the error-prone activity of reverse transcriptase, which is estimated to introduce an average of one error/genome/replication cycle (1), and recombination, which occurs at a rate of about 2%/kilobase/replication cycle (2).With the advent of international collaborations using powerful new tools that allow for the analyses of nucleotide sequence information, it became apparent that the initial classification of HIV into HIV-1 and HIV-2 based on geographic distribution was inadequate.We now recognize that HIV-1 can be divided into three major phylogenetic groups: 'M' (major), 'O' (outlier) and more recently, 'N' (new).The vast majority of isolates cluster in the M group.Based on sequencing the envelope gene, env, 10 phylogenetic subtypes (A to J) have been identified within this group, with subtypes A to E (also referred to as the circulating recombinant A/E) being the most common (3).The general pattern of subtype distribution by geographic location is shown in Table 1.The second major group of HIV-1, group O, is found mainly in Cameroon and Gabon, and differs from the M group by as many as 50% of residues (4).The N group of HIV-1 was isolated in Cameroon, with genetic characteristics of both the simian immunodeficiency virus and HIV-1 (M group) (5).Although there has been no systematic surveillance for ge-
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".