El asesoramiento genético: evolución, actualidad y retos en la era genómica
Bibliographic record
Abstract
Introduction: Genetic counseling is a patient/client centered communication process with the aim of helping them understand, adapt and adjust to the medical and psychosocial consequences of genetic contributions to the disease.Objective: To describe the evolution of the concept, models of genetic counseling and the profession of the genetic counselor from its inception to the current stage called the "genomic era" and its new challenges.Material and Methods: A systematization was carried out on the basis of reflective and critical reading on the subject. Publications without previous time limit and until 2020 were selected. Individual experience in teaching, medical assistance and research on the subject was also taken into account.Development: Analyses and assessments are made in relation to new concepts and practical models of genetic counseling, the profession of genetic counselor and services, genetic counseling in the genomic era and ethical aspects.Conclusions: Genetic counseling, in more than half a century of formal practice influenced by a variety of social, cultural, historical, local - regional and technical factors has evolved in its objectives and scope. The new (genomic) counselors will have to face new ethical dilemmas such as: the decision to communicate secondary findings; the potential for uncertainty from the large amount of data generated by genomic technologies; and the possible violation of privacy, discrimination, stigmatization and abuse based on the use of genomic information.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".