Bibliographic record
Abstract
On 23 January 1973 another diplomatic process, which had lasted years rather than months, reached its end: Henry Kissinger, for the United States, and Le Due Tho, for North Vietnam, initialled an Agreement on Ending the War and Restoring Peace in Vietnam. As the title implies, the purpose was much the same as that of the 1954 Geneva Agreements, but the terms were rather different. The cease-fire was to be ‘in place’ with no provision for the withdrawal of North Vietnamese forces from the South. No dates had been agreed for a cease-fire in either Cambodia or Laos and the Vietnamese later neither admitted nor implemented the undertaking they were supposed to have given separately to withdraw their forces from these two countries. International supervision of the cease-fire and of restrictions on reinforcement or resupply was entrusted to a balanced commission of Canada, Indonesia, Hungary and Poland fettered by the principle of unanimity. American forces, instead of being ready to withdraw, as the French had been in 1954, when so requested by the government in Saigon, were to be out of the country in two months. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.589 | 0.283 |
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".