Clouds, airplanes, trucks and people: carrying radioisotopes to and across Mexico
Bibliographic record
Abstract
The aim of this paper is to describe the early stages of Mexican nuclearization that took place in contact with radioisotopes. This history requires a multilayered narrative with an emphasis in North-South asymmetric relations, and in the value of education and training in the creation of international asymmetrical networks. Radioisotopes were involved in exchanges with the United States since the late 1940s, but also with Canada. We also describe the context of implementation of Eisenhower's Atoms for Peace initiative in Mexico that opened the door to training programs at both the Comisión Nacional de Energía Nuclear and the Universidad Nacional Autónoma de México. Radioisotopes became the best example of the peaceful applications of atomic energy, and as such they fitted the Mexican nuclearization process that was and still is defined by its commitment to pacifism. In 1955 Mexico became one of the 16 members of the atomic fallout network established by the United Nations. As part of this network, the first generation of Mexican (women) radio-chemists was trained. By the end of the 1960s, radioisotopes and biological markers were being produced in a research reactor, prepared and distributed by the CNEN within Mexico. We end up this paper with a brief reflection on North-South nuclear exchanges and the particularities of the Mexican case.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".