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Record W4406782167 · doi:10.1038/s44303-024-00056-w

Molecular imaging of viral pathogenesis and opportunities for the future

2025· review· en· W4406782167 on OpenAlexafffund
Brianna Kelly, Jeanette E. Boudreau, Steven Beyea, Kimberly Brewer

Bibliographic record

Venuenpj Imaging · 2025
Typereview
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsBeatrice Hunter Cancer Research InstituteIzaak Walton Killam Health CentreDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaIWK Health Centre
KeywordsMolecular imagingPathogenesisComputational biologyViral pathogenesisViral infectionMolecular virologyMolecular diagnosticsDiseaseMedicineBiologyVirologyBioinformaticsPathologyVirusGeneticsViral replication

Abstract

fetched live from OpenAlex

Molecular imaging is used in clinical and research settings. Since tools to study viral pathogenesis longitudinally and systemically are limited, molecular imaging is an attractive and largely unexplored tool. This review discusses molecular imaging probes and techniques for studying viruses, particularly those currently used in oncology that are applicable to virology. Expanding the repertoire of probes to better detect viral disease may make imaging even more valuable in (pre-)clinical settings.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.048
GPT teacher head0.365
Teacher spread0.316 · 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 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

Citations3
Published2025
Admission routes2
Has abstractyes

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