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Record W7010043725

Hipertensión Arterial en Argentina. Transición y Mortalidad Diferencial. Una estimación indirecta a partir de datos transversales (2009-2013).

2018· dissertation· es· W7010043725 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2018
Typedissertation
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsPersonaWork (physics)Data collectionQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Este trabajo se propone aportar información sobre la Hipertensión Arterial (HTA) en Argentina durante el período 2009-2013 en las edades 30 a 70 estimando de manera indirecta la probabilidad de transición hacia la HTA, la mortalidad diferencial asociada, y las esperanzas de vida con y sin HTA, que pueden ser insumo para la toma de decisiones en políticas de prevención. Se realizó una estimación indirecta basada en Guillot y Yu (2009). Los resultados principales indican que la probabilidad de ser hipertenso aumenta más de 5 veces iniciada la adultez mayor, ingresando anualmente a la HTA casi un 2% de los adultos entre 30 y 70 años, según estimaciones para el período 2009/2013. La esperanza de vida a los 30 años, temporaria hasta los 70 años, fue de un 8,6% menor en las personas con HTA. El porcentaje de años con HTA que esperaba vivir una persona de edad 30 hasta cumplir 70 años, independientemente de su estado inicial, fue del 36%.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.030
GPT teacher head0.308
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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