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Record W4252264794 · doi:10.3410/f.13371099.15273060

Faculty Opinions recommendation of A potent and broad neutralizing antibody recognizes and penetrates the HIV glycan shield.

2012· dataset· en· W4252264794 on OpenAlexfundno aff
Ajit Varki, Vered Padler‐Karavani

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2012
Typedataset
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
FundersSLAC National Accelerator LaboratoryBiological and Environmental ResearchBasic Energy SciencesNational Institute of Allergy and Infectious DiseasesNational Center for Research ResourcesInternational AIDS Vaccine InitiativeNational Institute of General Medical SciencesEngineering and Physical Sciences Research CouncilCanadian Institutes of Health ResearchNational Cancer InstituteRagon Institute of MGH, MIT and HarvardOffice of ScienceNational Institutes of HealthU.S. Department of Energy
KeywordsGlycanHuman immunodeficiency virus (HIV)AntibodyChemistryVirologyPolitical scienceMedicineGlycoproteinImmunologyBiochemistry

Abstract

fetched live from OpenAlex

The HIV envelope (Env) protein gp120 is protected from antibody recognition by a dense glycan shield.However, several of the recently identified PGT broadly neutralizing antibodies appear to interact directly with the HIV glycan coat.Crystal structures of Fabs PGT 127 and 128 with Man 9 at 1.65 and 1.29 Å resolution, respectively, and glycan binding data delineate a specific high mannose binding site.Fab PGT 128 complexed with a fully-glycosylated gp120 outer domain at 3.25 Å reveals that the antibody penetrates the glycan shield and recognizes two conserved glycans as well as a short β-strand segment of the gp120 V3 loop, accounting for its high binding

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.050
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0500.049

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 head0.044
GPT teacher head0.373
Teacher spread0.329 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueFaculty Opinions – Post-Publication Peer Review of the Biomedical LiteratureSame topicHepatitis B Virus StudiesFrench-language works237,207