Bibliographic record
Abstract
On December 8, 1953, President Dwight Eisenhower proposed in a speech to the United Nations that nuclear nonproliferation be promoted by offering peaceful nuclear technology to countries that would renounce nuclear weapons. Today the value of that basic trade-off-atoms for peace-is in question, along with the institutions that embody it. Deployment of weapons by India and Pakistan, noncompliance with safeguards by North Korea and Iran, and the threat of nuclear terrorism have weakened the image of the Nonproliferation Treaty. And new proposals and technologies for peaceful uses of nuclear power are coming forward, though they are accompanied by the realization that 1950s hopes for nuclear energy too cheap to meter were unrealistic. The twenty-five contributors to Atoms for Peace grapple in many ways with nuclear proliferation, nuclear terrorism, and the future of nuclear energy. They include officials and scientists from a wide range of agencies and institutions. Among them are officials or former officials from Israel, Egypt, Pakistan, Canada, Korea, and Japan, from the U.S. departments of state, energy, and defense, the U.S. Senate, the National Security Council, the U.S. Arms Control and Disarmament Agency, the International Atomic Energy Agency, the United Nations, the Nuclear Threat Initiative, MIT, Los Alamos National Laboratory, the College of William and Mary, and the University of California. Atoms for Peace also includes a set of fundamental speeches and documents relating to Atoms for Peace and its institutions.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".