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Record W2781532966

EXPOCIENCIAS INTERNACIONAL 2009

2015· article· es· W2781532966 on OpenAlexaboutno aff
Leonor Cristina Mojica Sánchez

Bibliographic record

VenueREVISTA CIENTÍFICA GUARRACUCO · 2015
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicLaw, Ethics, and AI Impact
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Con un exito rotundo se llevo a cabo la EXPO-SCIENCES­ INTERNATIONALE (ESI, 2009), realizada en Tunez del 23 al 29 de julio de este ano, con una concurrida participacion, mas de 44 paises entre los cuales se encontraba Taiwan, Argelia, Kuwait, Estados Unidos, Fran­cia, Letonia, Eslovaquia, Malta, Chile, etc. Todos los continentes reunidos a traves de mas de 1000 jovenes que intercambiaron conocimiento, cultura y amistad. Las delegaciones mas numerosas las conformaron Mexico, Brasil y Canada. La delegacion espanola, conformada por 21 jovenes participantes y 6 Asesores, presentaron 17 proyectos relacionados con diversas areas tematicas: fisica y astronomia, historia, ciencias, literatura, matematicas, ingenieria, deporte, educacion, etc. La delegacion arribo el dia 23 de julio a las instalaciones del evento con el fin de instalar los stands correspondientes con el material necesario. Nuestra delegacion fue la mas representativa en cuanto a simbolos se refiere. Cada stand de los participantes se acompano con las diferentes bande­ras de la Union Europea, Espana y la correspondiente a cada comunidad: Castilla y Leon, Cataluna, etc., y el escudo de INICE (Instituto de Investi­gaciones Cientificas y Ecologicas), la asociacion que dirige el grupo de Jovenes Investigadores en Espana y que nos da la oportunidad de asistir a este tipo de encuentros internacionales gracias a su amplia y reconocida trayectoria (en mi stand, adicionalmente, estuvo el escudo de la Corporacion Universitaria del Meta). La participacion de Espana fue muy destacada en sus proyectos: algunos premiados, otros muy concurridos, en general todos muy destacados dentro de las variadas actividades culturales alter­nas a la exposicion y se creo un ambiente de mayor integracion entre los participantes.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.241
Threshold uncertainty score0.806

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2410.103

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 head0.057
GPT teacher head0.291
Teacher spread0.234 · 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
Published2015
Admission routes1
Has abstractyes

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