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Record W3200513302

Ácido salicílico: una hormona vegetal que nos ha ahorrado más que un dolor de cabeza

2019· article· es· W3200513302 on OpenAlexaff
Edel Pérez‐López

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2019
Typearticle
Languagees
FieldMedicine
TopicNatural Products and Biological Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTraditional medicineMedicineHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

\nLas propiedades medicinales del ácido salicílico han sido conocidas desde hace al menos 1 300 años. Restos arqueológicos encontrados en Norteamérica y Asia indican que estas culturas usaban infusiones de corteza de sauce para tratar fiebres. Pero no fue hasta 1828 que el químico alemán Johann Andreas Buchner aisló y nombró el compuesto “salicina”, a partir del nombre científico del sauce blanco (Salix alba). Este sauce es nativo de zonas templadas, también se ha naturalizado en zonas subtropicales y cultivado en los trópicos.\nAdemás de ser muy popular como ingrediente activo de la aspirina, el principal uso del ácido salicílico en la medicina es como parte de un gran número de productos de uso dermatológico para tratar acné, psoriasis, callosidades y callos, queratosis, acantosis, ictiosis y verrugas. El ácido salicílico es también parte de los medicamentos usados para aliviar el dolor de estómago, medicamentos antiinflamatorios, así como medicamentos destinados a reducir el dolor muscular.--LEER MÁS--

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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