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Record W2088668371 · doi:10.3791/2531

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

2010· article· en· W2088668371 on OpenAlexafffund
Rachel A. McGovern, P. Richard Harrigan, Luke C. Swenson

Bibliographic record

VenueJournal of Visualized Experiments · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsAIDS Vancouver
FundersCanadian Institutes of Health ResearchViiV HealthcareGlaxoSmithKlinePfizer
KeywordsGenotypeBiologyInferenceHuman immunodeficiency virus (HIV)PopulationTropismComputational biologyVirologyGeneticsMedicineComputer scienceVirusGeneArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Prior to receiving a drug from CCR5-antagonist class in HIV therapy, a patient must undergo an HIV tropism test to confirm that his or her viral population uses the CCR5 coreceptor for cellular entry, and not an alternative coreceptor. One approach to tropism testing is to examine the sequence of the V3 region of the HIV envelope, which interacts with the coreceptor. METHODS: Viral RNA is extracted from blood plasma. The V3 region is amplified in triplicate with nested reverse transcriptase-PCR. The amplifications are then sequenced and analyzed using the software, RE_Call. Sequences are then submitted to a bioinformatic algorithm such as geno2pheno to infer viral tropism from the V3 region. Sequences are inferred to be non-R5 if their geno2pheno false positive rate falls below 5.75%. If any one of the three sequences from a sample is inferred to be non-R5, the patient is unlikely to respond to a CCR5-antagonist.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.431
Teacher spread0.382 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2010
Admission routes2
Has abstractyes

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