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Record W2803395914

Obra plástica de Cecilia Vázquez

2017· article· es· W2803395914 on OpenAlexaboutno aff
Cecilia Vázquez

Bibliographic record

VenueInventio, la génesis de la cultura universitaria en Morelos · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicTechnology in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities
DOInot available

Abstract

fetched live from OpenAlex

Artista plastica originaria de la Ciudad de Mexico. Realizo estudios en Artes Visuales en la Escuela Nacional de Artes Plasticas (ENAP) de la Universidad Nacional Autonoma de Mexico (UNAM) y de Maestria en Bellas Artes en el Massachusetts College of Art and Design en Boston. Fue becaria del Fondo Nacional para la Cultura y las Artes (FONCA), asi como del programa de becas Fulbright-Garcia Robles. Renovo su permanencia en el Sistema Nacional de Creadores de Arte (SNCA) para el periodo 2013-2015. Ha sido artista residente en la Fundacion Arte y Artistas Contemporaneos en Espana, en el Banff International Centre for the Arts en Canada y en el New York Arts Beijing en China. En contraposicion a las corrientes del arte conceptual y posconceptual, a partir de su residencia artistica en Boston ha orientado su practica plastica y vital desde un enfoque abstracto. Se ha replanteado la pintura como resultado de la representacion de equilibrios visibles en las transiciones contrapuestas de amor/ira y vida/muerte. En sus ultimas obras ha colocado por primera vez flores en sus pinturas, tanto en el sentido de seduccion como en el de ofrenda, que se contrastan con visceras, intestinos e higados, los cuales constituyen indicios de su lenguaje visual: disimil pero armonico, sutil pero impulsivo y voluptuoso, con una tecnica cuidadosa, lograda, que presenta en grandes formatos.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0350.004

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 head0.015
GPT teacher head0.363
Teacher spread0.348 · 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
GenreOther

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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