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Record W2157380267 · doi:10.1586/ers.12.8

Identifying targets in the hunt for effective respiratory syncytial virus interventions

2012· review· en· W2157380267 on OpenAlexaff
Farnoosh Tayyari, Richard G. Hegele

Bibliographic record

VenueExpert Review of Respiratory Medicine · 2012
Typereview
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsHospital for Sick ChildrenCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsMedicinePalivizumabPsychological interventionVirusIntensive care medicineImmunologyVirologyRespiratory systemIncidence (geometry)Internal medicine

Abstract

fetched live from OpenAlex

Respiratory syncytial virus (RSV) is a major cause of human infections worldwide. There is currently no effective vaccine or antiviral therapy available for widespread clinical use; prophylaxis with anti-RSV antibodies is used in only a small percentage of potential recipients. New targets for effective RSV interventions are needed. Previous anti-RSV intervention strategies have focused on targeting aspects of the virus, an approach that can lead to the emergence of resistant RSV strains. Increased understanding of the biology of RSV-host interactions provides an alternative approach for identifying novel targets for RSV interventions that focus on host factors, and exploiting them with the aim to limit the incidence and severity of RSV infections.

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)0.012
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.277
GPT teacher head0.545
Teacher spread0.269 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2012
Admission routes1
Has abstractyes

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