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Record W2735271087

ESTUDIANTES DE INGENIERÍA, EN POS DEL PETROBOWL

2016· article· es· W2735271087 on OpenAlexaboutno aff
René Tijerino

Bibliographic record

VenueGaceta UNAM (2010-2016) · 2016
Typearticle
Languagees
FieldSocial Sciences
TopicSocial impacts of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical science
DOInot available

Abstract

fetched live from OpenAlex

TRAS OBTENER PLATA EN LA COMPETENCIA REGIONAL EN AUSTIN, TEXAS, LOS ALUMNOS DE LA FACULTAD DE INGENIERIA ERNESTO QUETZALLI MAGANA, ALONSO MAGOS, MA­RIO FERNANDO CORDOVA, ENRIQUE AVILA Y JULIO CESAR VILLANUEVA SE PREPARAN PARA REFRENDAR EL ORO GANADO POR LA UNAM EN EL PETROBOWL DEL ANO PASADO. EN ESTA OCASION LA JUSTA SE REALIZARA EN SEPTIEMBRE EN DUBAI. CON ESTE OBJETIVO, CADA SEMANA LOS JOVENES SOSTIENEN REUNIONES CON SU MENTOR, FERNANDO SAMANIEGO VERDUZ­CO, Y CON LOS COACHES CESAR LUIS MEZA OROZCO Y EDER CASTANEDA CORREA, EXA­LUMNOS CON EXPERIENCIA EN ESAS JUSTAS. LOS CONTENDIENTES PUMA –DE LA CARRERA INGENIERIA PETROLERA– RECOR­DARON QUE LA UNAM HA PARTICIPADO EN ESTE CERTAMEN MUNDIAL DESDE 2010. AUNQUE TRES DE ELLOS FORMARON PARTE DE LA ESCUADRA CAMPEONA DE 2015, LA ETIQUETA DE MONARCA NO PESO EN AUSTIN, DONDE ENFRENTARON A 26 UNIVERSIDADES DE CANADA, ESTADOS UNIDOS Y MEXICO. CONFIADOS EN SUS CONOCIMIENTOS Y PREPARACION, DESEAN SER BICAMPEONES Y SEGUIR LOS PASOS DE LAS UNIVERSIDADES ESTADUNIDENSES DE OKLAHOMA (QUE LO­GRO ESTA PROEZA EN 2007-2008) Y LA DE MINAS DE COLORADO (2012-2013). LAS SESIONES DE ENTRENAMIENTO SE PROLONGARAN HASTA SEPTIEMBRE Y CONS­TARAN DE REVISIONES DE PAPERS , LIBROS SOBRE HISTORIA DEL PETROLEO, DOCUMEN­TOS TECNICOS, NOTICIAS, ESTADISTICAS DE CONSUMO Y ASUNTOS RELACIONADOS CON LA PRODUCCION DE HIDROCARBUROS. EL PETROBOWL 2016 FORMA PARTE DE LA ANNUAL TECHNICAL CONFERENCE AND EXHIBITION Y SE HARA DEL 24 AL 27 DE SEPTIEMBRE EN DUBAI.

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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.003
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.003

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 head0.025
GPT teacher head0.326
Teacher spread0.301 · 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
Published2016
Admission routes1
Has abstractyes

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