MétaCan
Menu
Back to cohort

Genotoxicity evaluation of gene therapies: highlights from IWGT 2022

2024· preprint· en· W4401885706 on OpenAlexaboutno aff
Silvana Libertini, Julie K. Jadlowsky, Thomas A. Lanz, Lauren Mihalcik, Daniella Pizzurro

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsGenotoxicityTransparency (behavior)Session (web analytics)Computational biologyMedicineBioinformaticsComputer scienceBiologyWorld Wide WebInternal medicine

Abstract

fetched live from OpenAlex

At the 8th International Workshop on Genotoxicity Testing (IWGT) meeting in Ottawa, August 2022, a plenary session was dedicated to the genotoxicity risk evaluation of gene therapies, including insertional oncogenesis and off-target genome editing. This brief communication summarizes the topics of discussion and the main insights from the speakers. Common themes included recommendations to conduct tailored risk assessments based on a weight of evidence approach, to promote data sharing, transparency, and cooperation between stakeholders, and to develop state-of-the-art validated tests relevant to clinical scenarios.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.064
GPT teacher head0.353
Teacher spread0.289 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicBiomedical Ethics and RegulationFrench-language works237,207