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Record W4206161665 · doi:10.15446/rsap.v23n2.88369

El Sistema de Salud Colombiano y el reconocimiento de la enfermedad de Alzheimer

2021· article· es· W4206161665 on OpenAlexaff
Sara Julieta Romero Vanegas, Juan‐Camilo Vargas‐González, Rodrigo Pardo, Javier Eslava‐Schmalbach, Marisol Moreno Angarita

Bibliographic record

VenueRevista de Salud Pública · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsWestern University
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La enfermedad de Alzheimer (EA) es la más común de las demencias; es un problema de salud pública en el Mundo, pero en Colombia no hace parte de las prioridades del Estado. El presente ensayo aborda cómo el sistema de salud colombiano reconoce, identifica y provee servicios a los pacientes con EA, desde una óptica de la Justicia Social. En primera medida se evalúa la información generada por la academia, su correlato con la normativa vigente y su articulación. Se explora la lógica utilitarista del sistema de salud colombiano y el incentivo a la maximización de ganancias de los aseguradores y cómo esto ha llevado a los pacientes a exigir la restitución de derechos a través de la acción de tutela. Se explora el sistema de codificación y diagnostico usado para la generación de información y como esta es imprecisa en los canales de información consolidada. Por otra parte, se valora como el rol de la familia se hace parte fundamental del proceso, y cómo esta termina siendo víctima del mismo. Finalmente, se plantea reflexiones de cómo pueden abordarse las dificultades identificadas desde una perspectiva de la Justicia Social.

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)0.005
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.287
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.004
Scholarly communication0.0120.005
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.061
GPT teacher head0.423
Teacher spread0.362 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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Same venueRevista de Salud PúblicaSame topicPublic Health and Social InequalitiesFrench-language works237,207