¿Cuál es su perfil inversor? Ponga su patrimonio a buen recaudo
Bibliographic record
Abstract
La mayoria de los denominados como ahorradores-inversores basan las decisiones sobre sus recursos en una progresion pasada o, como mucho, de futuro a corto plazo. Este sistema, aunque valido, se queda corto a la hora de proteger adecuadamente los intereses financieros no solo en el presente, sino tambien en un futuro que nos sobreviva: nuestros herederos. Este articulo pretende servir de recordatorio sobre la importancia de la proteccion de nuestro patrimonio dentro de estructuras ad hoc, tanto de planificacion financiera mediante carteras bien construidas, como de coberturas de riesgo por medio de seguros. Todo ello para hacer frente, con activos bien gestionados, a las diferentes necesidades en cada etapa de la vida. Ademas, les proponemos un ejercicio de autoevaluacion para que conozca cual es su perfil de inversor: conservador, equilibrado o dinamico
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".