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Record W4410551380 · doi:10.1089/crispr.2025.0058

A Reset for Bioethics: A Statement from the Global Observatory for Genome Editing

2025· article· en· W4410551380 on OpenAlexaff
Sheila Jasanoff, J. Benjamin Hurlbut, Krishanu Saha, Jacob Moses, Daniel Affsprung, Henry Austin, Françoise Βaylis, John H. Evans, Tim D. Hunt, Douglas A. Kysar, Laurence Lwoff, Peter Mills, Jahnavi Phalkey, Matthew H. Porteus, O. Carter Snead, Kaushik Sunder Rajan, Carrie D. Wolinetz

Bibliographic record

VenueThe CRISPR Journal · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsRoyal Society of CanadaRoyal Ottawa Mental Health CentreDalhousie University
Fundersnot available
KeywordsStatement (logic)Reset (finance)BioethicsObservatoryGenome editingGenomeComputer scienceComputational biologyBiologyEpistemologyPhilosophyAstronomyGeneticsPhysicsBusiness

Abstract

fetched live from OpenAlex

How should we govern our increasing power to intervene in the processes of life? Genome editing, especially of the human germline, has brought this question to the forefront of global debate. We must seek to rectify shortcomings of earlier deliberative approaches by setting aside a science-and-technology first approach; expanding the range of questions for deliberation; revisiting the distribution of innovation's benefits and risks; and reimagining the limits of research. This Perspective from the Organizing Committee of the 2025 Global Observatory for Genome Editing International Summit calls for a new social compact, recognizing and rendering accountable the constitutive role of science and technology in shaping the meaning of human life in the 21st century.

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)0.084
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.084
Threshold uncertainty score0.443

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.085
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0130.031
Scholarly communication0.0190.022
Open science0.0050.015
Research integrity0.0670.112
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.394
Teacher spread0.358 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations5
Published2025
Admission routes1
Has abstractyes

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