Aspectos médicos y bioéticos en el asesoramiento genético del cáncer hereditario
Bibliographic record
Abstract
"Actualmente es posible la detección oportuna de enfermedades como el cáncer que, por años, han sido un problema de salud pública en el mundo. Se calcula que de 5 a 10% de todos los tumores tienen un patrón hereditario. La asesoría sobre cáncer hereditario, está modificado definitivamente la historia natural de algunos cánceres a través del asesoramiento genético y el estudio de algunos síndromes que predisponen al cáncer, lo cual incide positivamente en los índices de morbilidad y mortalidad de los mismos. El tratamiento bioético es primordial en la atención del cancer hereditario y debe estar centrado en la prevención temprana, afin de garantizar beneficio a los portadores, por medio del asesoramiento genético individual por parte del médico genetista y de un comité de bioética, claro, oportuno y convincente."
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".