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2005· article· en· W4234441387 on OpenAlexaboutno aff
Rony E. Duncan

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2005
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsGeneticistMedicineClinical PracticePsychoanalysisFamily medicinePsychology

Abstract

fetched live from OpenAlex

I am grateful to Ms Richards for sharing her personal experience in this area. My aim in the annotation piece was to briefly summarize existing guidelines concerning predictive genetic testing in young people for adult onset conditions and to outline some of the objections to these found in recent published work. In particular, there are three points raised by Ms Richards that I wish to address. First, Ms Richards notes that most of the published work I summarize that argues in favour of such testing has been written by people with no clinical experience in the area of predictive testing for HD. She then makes the strong contention that ‘Academic debate … may be acceptable but that the views of those with no clinical experience … should not be allowed to dictate clinical practice’. Few would agree with this claim. In fact, there are many areas of clinical practice where people who are not clinicians help to dictate practice. Health economists, lawyers, ethicists, politicians and the general public – medicine's stakeholders – all rightly contribute to clinical policy, as do the many researchers who are not clinicians. Policy is best dictated by a combination of all of the above, including clinicians. Authors putting forward arguments in favour of predictive testing in young people include Professor Peter Harper (Professor and Consultant in Medical Genetics),1 Professor Steven Roberston (Clinical Geneticist),2 Dr Julia Binedell (Clinical Psychologist),1 Dr Susan Michie (Reader in Clinical Health Psychology),3 Dr Jane Scourfield (Psychiatrist),1 Dr Jo Soldan (Clinical Psychologist),1 Neil Sharpe (member of the Genetic Testing Research Group, Canada)4 and Professor Julian Savulescu (Ethicist at the Oxford Uehiro Centre for Practical Ethics).2 Non-clinicians bring different but valuable expertise to the debate about predictive genetic testing in young people. It is also worth noting that several authors of existing guidelines (arguing against testing in young people) are not directly involved in predictive testing either; some work in Paediatrics, others in Law and others in Psychiatry.5 The opinions of non-clinicians should continue to be allowed to help dictate clinical policy, alongside the views of clinicians. Second, Ms Richards doubts that any young person under the age of 18 years would have the ‘maturity’ or ‘insight’ to undergo predictive testing and is not in favour of competency judgements replacing an age limit. However, current guidelines actually cite the possibility of providing such testing to a young person who is deemed competent. Published guidelines state that ‘substantial psychosocial benefits to the competent adolescent also may be a justification for genetic testing’.6 Guidelines even begin to outline what must occur for a young person to be deemed competent.7 Thus, my discussion of competency assessments was not a new one, I was summarizing existing guidelines. Finally, Ms Richards states that a need for psychological research is not an ethical reason for condoning the testing of minors. I agree entirely. The desire for empirical research specifically about predictive genetic testing in young people is strong.3, 5, 6, 8-11 However, it would only be ethical to research these outcomes if such testing was already occurring. Given that we now have evidence that such testing is occurring in several countries around the world, it is time for systematic empirical research to follow.12 In fact, it would be unethical not to conduct empirical research on the outcomes of such testing when the opportunity arises.

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)0.005
metaresearch head score (Gemma)0.048
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.072
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0060.007
Open science0.0030.004
Research integrity0.0220.032
Insufficient payload (model declined to judge)0.0720.051

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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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
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".

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Citations1
Published2005
Admission routes1
Has abstractyes

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