Management of sexual assault and the importance of Sexual Assault Referral Centres (SARCs)
Bibliographic record
Abstract
Increasing genetic knowledge over the last decade has enabled hundreds of genetic variants associated with inherited cardiac conditions to be identified, many of which cause increased risk of sudden cardiac death. While individually these conditions are rare, taken together they impose a significant burden. The severity of these conditions—the possibility that they might cause sudden unheralded death of a teenager or young adult—juxtaposed with uncertainty about the pathology linked with many of the genetic variants is significant in terms of professional practice because, increasingly, clinicians have been encouraged to cascade out genetic testing from the proband or consultand to other family members who may be at risk of developing the same condition. This process often involves sharing human tissue samples, DNA or personal information. This paper reviews the legal and regulatory frameworks which may apply when tissue and DNA samples are collected, used and retained, both for the purpose of diagnosis and for benefiting other family members, when a suspected or definitive diagnosis of an inherited cardiovascular condition is made. Sometimes the interests of family members may conflict, and it may be difficult for practitioners to reconcile the interests of one family member with another, particularly if the balance of benefits and harms from testing is unclear. The paper then examines some of the ethical tensions which may arise in practice and concludes that all involved should be conversant with the legal and ethical frameworks that apply.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".