Bibliographic record
Abstract
LA DEPORTISTA PUMA ANGELES BARRAZA QUEDO EN EL QUINTO LUGAR EN EL CAMPEONATO MUNDIAL UNIVERSITARIO DE LUCHA, EFECTUADO EN MAYO PASADO EN EDMONTON. DENTRO DE POCO MAS DE DOS MESES TENDR LA OPORTUNIDAD DE MEDIRSE CON LUCHADORAS DE OTROS PAISES, INCLUSO CON AQUELLAS QUE LA DERROTARON EN DICHO CAMPEONATO, LUEGO DE HABER PERMANECIDO FUERA DE ESTE TIPO DE COMPETENCIAS DURANTE DOS ANOS. ANGELES, DE CASI 24 ANOS DE EDAD, RECUERDA QUE AL COMENZAR A PRACTICAR ESTE DEPORTE JAMAS IMAGINO QUE FUERA UNA DISCIPLINA OLIMPICA. SENALA QUE EST EMPEZANDO A TRABAJAR NUEVAMENTE Y TRATAR DE ALCANZAR SU SUENO: ATENAS 2004. ANGELES ES ESTUDIANTE DE LA FACULTAD DE CONTADURIA Y ADMINISTRACION; DEBIDO A SU ESFUERZO, EN 1997 FUE GALARDONADA CON EL PREMIO PUMA, POR TENER UNO DE LOS MEJORES PROMEDIOS (9.50) Y SER UNA DE LAS MAS DESTACADAS DEPORTISTAS CON QUE CUENTA LA UNAM.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.019 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".