ACUERDAN UNIVERSIDADES DE MÉXICO, EU Y CANADÁ CREAR EJE DE COOPERACIÓN CIENTÍFICA
Bibliographic record
Abstract
EL RECTOR ENRIQUE GRAUE WIECHERS RECIBIO AYER EN SU OFICINA A PETER MCPHERSON, PRESIDENTE DE LA ASOCIACION DE UNIVERSIDADES PUBLICAS (APLU, POR SUS SIGLAS EN INGLES). EN ESTA VISITA SE ACORDO, ENTRE OTRAS COSAS, INICIAR LA ELABORACION DE UN CONVENIO EN FAVOR DE LA INVESTIGACION CIENTIFICA ENTRE LAS PRINCIPALES UNIVERSIDADES PUBLICAS DE LOS TRES PAISES QUE CONFORMAN EL TRATADO DE LIBRE COMERCIO: CANADA, ESTADOS UNIDOS Y MEXICO. MCPHERSON PUBLICO, EL PASADO 26 DE ENERO, UNA CARTA EN LA QUE AFIRMO QUE LAS UNIVERSIDADES ESTADUNIDENSES SE ENRIQUECEN Y SE FORTALECEN CON EL TALENTO, VISION Y LA CULTURA DE LOS ALUMNOS INTERNACIONALES, LOS CUALES DEBEN CONTINUAR SUS ESTUDIOS. ES EN ESTE CONTEXTO QUE LA UNAM Y LA APLU UNIRAN ESFUERZOS PARA CONVOCAR A SUS HOMOLOGOS Y CREAR LA ALIANZA DE UNIVERSIDADES EN FAVOR DE LA CIENCIA. LA APLU, FUNDADA EN 1887, ES LA ASOCIACION DE EDUCACION SUPERIOR MAS ANTIGUA DE EU Y ESTA COMPUESTA POR 238 UNIVERSIDADES PUBLICAS DE INVESTIGACION, INSTITUCIONES DE CONCESION DE TIERRAS Y SISTEMAS UNIVERSITARIOS DE ESTADOS UNIDOS, CANADA Y MEXICO.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".