Latin American Physicists Weigh In on Funding, Demographics, Potential
Bibliographic record
Abstract
I read with interest the article by José Luis Morán-López. He states that it is not complete; still, the newly released results of a study by Colciencias, the Colombian Science Foundation (http://www.colciencias.gov.co), necessitate a revision of Colombia’s entry in the table on page 40.Almost 750 research groups in all disciplines (natural, social, and applied sciences, and humanities) participated in the study. Sixty-nine of them were ranked in the highest category based on publications in international journals. Of these groups, 17 (one-quarter) work in physics or related areas. Four universities—Antioquia, Valle, the Andes, and National—have at least three top-ranked physics groups each. Three others—Cauca, the Industrial University of Santander, and Quindio—have one group each.Many of these research groups contribute to the early training of young scientists, who often publish their first papers while working with them, and many groups have long-term collaborations with major institutes or universities throughout the world. While the international effect of Colombian physics may be modest, the few hundred physics PhDs in this country have a significant impact on the local research community of about 4000 individuals.© 2001 American Institute of Physics.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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.
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".