Making the Decision to Participate in Predictive Genetic Testing for Arrhythmogenic Right Ventricular Cardiomyopathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper describes the experience of predictive genetic testing for Arrhythmogenic Right Ventricular Cardiomyopathy in the context of novel gene discovery. Two approaches to making the decision to engage in genetic testing were apparent: the decision to be tested either (a) develops gradually over time or (b) happens so quickly that it is felt as a "fait accompli." Six key factors that influenced the particular approach taken by the participants were identified: (1) scientific process--available and relevant predictive genetic test; (2) numerous losses or deaths within the family; (3) physical signs and symptoms of disease; (4) gender; (5) sense of relational responsibility or moral obligation to other family members; and (6) family support. This study found that at risk individuals juxtapose scientific knowledge against their experiential knowledge and the six identified factors in order to make the decision to participate in genetic testing. Recommendations include the creation of a relational space within which to provide psychological counselling and assessment for the six identified factors that shape the decision to engage in predictive genetic testing.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it