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Record W2008641281 · doi:10.1038/sj.mt.6300316

Stable Ethics: Enrolling Non-Treatment-Refractory Volunteers in Novel Gene Transfer Trials

2007· article· en· W2008641281 on OpenAlexaff
Jonathan Kimmelman

Bibliographic record

VenueMolecular Therapy · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineClinical trialDiseaseGenetic enhancementPsychological interventionEnzyme replacement therapyOrnithine transcarbamylase deficiencyAdenosine deaminase deficiencyAdverse effectIntensive care medicinePediatricsFamily medicineInternal medicineAdenosine deaminasePsychiatryGeneBiologyGenetics

Abstract

fetched live from OpenAlex

The vast majority of human gene transfer experiments have been tested in patients suffering from advanced, treatment-refractory diseases. Until recently, some jurisdictions actually restricted gene transfer trials to “disorders that are life threatening or cause serious handicap and for which treatment is either unavailable or unsatisfactory.”1 However, some of the best opportunities for advancing knowledge have involved diseases for which standard, if suboptimal, medical interventions are available.

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)0.456
metaresearch head score (Gemma)0.373
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.670

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4560.373
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0070.007
Open science0.0040.005
Research integrity0.0170.011
Insufficient payload (model declined to judge)0.0070.004

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 head0.065
GPT teacher head0.365
Teacher spread0.300 · 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.

Study designTheoretical or conceptual
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

Citations18
Published2007
Admission routes1
Has abstractyes

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