Bibliographic record
Abstract
Spa: El Grupo de Investigación en Catálisis fue creado en el año 1997 gracias a sus gestores el Dr HUGO ALFONSO ROJAS SARMIENTO y la Dra. GLORIA DEL CARMEN BORDAGUERRA. Desde esta época se ha caracterizado por su espíritu emprendedor y su gran interés por la investigación. En la actualidad cuenta con 19 integrantes, 5 de los cuales son docentes de la Universidad Pedagógica y Tecnológica de Colombia, 1 docente de la Universidad Nacional de Colombia, 1 docente de la Universidad de Concepción-Chile, 2 estudiantes de maestría, 1 Joven investigador y 9 estudiantes de pregrado que integran el semillero de investigación del grupo. En cabeza de su director el Dr. HUGO ALFONSO ROJAS SARMIENTO el grupo de Catálisis, con el paso de los años ha logrado establecer alianzas estratégicas con universidades nacionales e internacionales, tal es el caso de la Universidad Nacional de Colombia, Universidad Central, Universidad de Concepción – Chile y el Instituto de Catálisis y Petroleoquímica de Madrid, España (CSIC); en colaboración con el Dr. Jesús Sigifredo Valencia Ríos, Dra. Yaneth Vásquez, Dr. Patricio Reyes Nuñez y el Dr. José Luis García Fierro, respectivamente.
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 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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.034 |
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".