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Manual para la evaluación de tecnologías sanitarias, versión corta

2022· article· W7133317017 on OpenAlex
Reyes Nora, Karen Inés Fasabi Huamán, Fernando Coronado-Dávila, Verónica Peralta, José A. Zavala-Loayza, Juana Gómez, Jenner I. Solís, Daniel E Rojas-Bolivar, Romina A. Tejada, Ericson L. Gutiérrez

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista del Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo · 2022
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsContext (archaeology)Relation (database)

Abstract

fetched live from OpenAlex

El objetivo de este artículo es presentar las pautas metodológicas establecidas en el manual de Evaluaciones Tecnológicas Sanitarias Cortas, que fueron desarrolladas por la Red Nacional de Evaluación de Tecnologías Sanitarias del Perú. El propósito del manual es estandarizar las metodologías de desarrollo de las Evaluaciones Tecnológicas Sanitarias Cortas entre las instituciones de evaluación de tecnologías de salud. Con la elaboración de este manual se busca contribuir a la toma de decisiones informada en evidencia para mejorar el acceso de la población a tecnologías sanitarias seguras y eficaces en el país.

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 imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.004

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 head0.122
GPT teacher head0.396
Teacher spread0.274 · 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