Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nuclear command and control increasingly relies on computing networks that might be vulnerable to cyber attack. Yet nuclear deterrence and cyber operations have quite different political properties. For the most part, nuclear actors can openly advertise their weapons to signal the costs of aggression to potential adversaries, thereby reducing the danger of misperception and war. Cyber actors, in contrast, must typically hide their capabilities, as revelation allows adversaries to patch, reconfigure, or otherwise neutralize the threat. Offensive cyber operations are better used than threatened, while the opposite, fortunately, is true for nuclear weapons. When combined, the warfighting advantages of cyber operations become dangerous liabilities for nuclear deterrence. Increased uncertainty about the nuclear/cyber balance of power raises the risk of miscalculation during a brinksmanship crisis. We should expect strategic stability in nuclear dyads to be, in part, a function of relative offensive and defensive cyber capacity. To reduce the risk of crisis miscalculation, states should improve rather than degrade mutual understanding of their nuclear deterrents.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it