MétaCan
Menu
Back to cohort
Record W4409781274 · doi:10.1684/vir.2025.1084

The 16th Annual International Oncolytic Virotherapy Conference (IOVC) in Rotterdam: For the dreamers and doers of oncolytic virotherapy

2025· article· en· W4409781274 on OpenAlexaff
David Olagnier, Tommy Alain

Bibliographic record

VenueVirologie · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOncolytic virusVirotherapyResilience (materials science)MedicineVirologyVirusPhysics

Abstract

fetched live from OpenAlex

From October 27-30 2024, the 16th International Oncolytic Virotherapy Conference (IOVC) was held in Rotterdam, the Netherlands, a city that mirrors the spirit of resilience, conviction, and innovation of researchers in the field of oncolytic viruses. Rotterdam, renowned for its post-war rebuilding with cutting-edge architecture designed for a bright future in mind, provided a fitting reflection that oncolytic virotherapy is at a turning point in its evolution. Hosted at the International Congress Center De Doelen, the event gathered clinicians, scientists, and biotech leaders to showcase the most up-to-date clinical applications, novel viral platforms, targeted mechanisms, and immune-modulating strategies that will push the boundaries of cancer immunotherapy into the next era. We present here an overview of this engaging meeting and offer our own perspectives on where to dream and continue to build.

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)0.004
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0410.012

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 head0.019
GPT teacher head0.344
Teacher spread0.325 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueVirologieSame topicVirus-based gene therapy researchFrench-language works237,207