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Record W3150810260 · doi:10.1139/facets-2020-0062

Clinical translation of mitochondrial replacement therapy in Canada: a qualitative study of stakeholders’ attitudes

2021· article· en· W3150810260 on OpenAlexaffvenueabout
Forough Noohi, Miranda Li, Yann Joly

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsTerminologyThematic analysisQualitative researchEthical issuesPsychologyKnowledge translationPublic healthPolitical scienceMedical educationPublic relationsMedicineEngineering ethicsCriminologySociologyNursingSocial scienceEngineering

Abstract

fetched live from OpenAlex

Mitochondrial replacement therapy (MRT) in Canada is considered a criminal offense according to article 5(1)(f) of the Assisted Human Reproduction Act (AHRA) (2004). The Act prohibits any practice that modifies the genome of “a human being or in vitro embryo such that the alteration is capable of being transmitted to descendants.” We carried out 32 semi-structured interviews with clinicians, researchers, patient groups, egg donors, and members of the public to explore their attitudes toward the clinical implementation of MRT in Canada. Our interview guide was informed by the socio-ethical, legal, and scientific literature of MRT. We used a thematic analysis to identify and analyze emerging themes and sub-themes. Our findings were divided into five broad themes: ( i) an outdated criminal ban, ( ii) motives for using MRT, ( iii) terminology, ( iv) practical and theoretical risks and benefits, and ( v) the feasibility of clinical translation in Canada. Although the public and stakeholders’ views on the feasibility of foreseeable translation of MRT in Canadian clinics varied, there was consensus on conducting an overdue review of the current AHRA ban on MRT.

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)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0280.015
Scholarly communication0.0060.003
Open science0.0030.006
Research integrity0.0030.006
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 head0.108
GPT teacher head0.379
Teacher spread0.271 · 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 designQualitative
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

Citations5
Published2021
Admission routes3
Has abstractyes

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Same venueFACETSSame topicMetabolism and Genetic DisordersFrench-language works237,207