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Record W2608327320 · doi:10.1063/1.4796339

Latin American Physicists Weigh In on Funding, Demographics, Potential

2001· article· en· W2608327320 on OpenAlexaboutno aff
Penélope Rodríguez

Bibliographic record

VenuePhysics Today · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEducational Research and Science Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsDemographicsLibrary scienceLatin AmericansQuarter (Canadian coin)PublicationPolitical scienceGeographySociologyDemographyArchaeology

Abstract

fetched live from OpenAlex

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.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0180.003

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 head0.042
GPT teacher head0.298
Teacher spread0.256 · 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.

Study designObservational
DomainIncentives
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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