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Record W3087427562

Metástasis: un hito para el conocimiento, un reto para la ciencia

2020· article· es· W3087427562 on OpenAlexaff
Alejandro Guerra González, Eduardo Silva, S. Montero, Dani J. Rodríguez, Ricardo Mansilla, José Manuel Villar

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languagees
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

RESUMEN Introducción: La metástasis del cáncer es la transferencia de células tumorales de un órgano a otro mediante una serie de multipasos secuenciales interrelacionados. Este proceso es uno de los principales retos en el tratamiento del cáncer debido a su heterogeneidad biológica. El proceso de metástasis es considerado la principal causa de muerte en esta enfermedad, reportándose que más de 90 % de las muertes por cáncer son debidos a esta etapa. Objetivo: Actualizar los conocimientos sobre metástasis en tumores sólidos y su asociación con transición epitelial-mesenquimal (EMT) en relación a la evolución y emergencia del cáncer. Método: Se realizó una revisión, no sistemática, de los estudios más significativos sobre el tema, publicados en la Web of Science, Pubmed, Ebsco, Scopus e Infomed. Conclusiones: La metástasis es la principal causa de muerte del cáncer, por lo que entender las bases del mecanismo de la formación de tumores metastásicos permitirá realizar terapias más eficaces para tratar el cáncer.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0020.009
Scholarly communication0.0120.010
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.004

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 head0.330
GPT teacher head0.568
Teacher spread0.238 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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