Bibliographic record
Abstract
On May 24 – 25th 2004 senior officers from Europe, the United States and Canada met at Senningen Chateau in Luxembourg for the first meeting of what was termed the ‘Africa Clearing House’. Europe was represented by Britain, France, Germany, Belgium, Ireland, Italy, Greece, Portugal, Spain, the Netherlands, Luxembourg and Austria (representing the UN’s Standby High Readiness Brigade Shirbrig). Also in attendance were representatives of Nato and the European Union. The conference, co-hosted by the U.S. and Luxembourg and took as its focus West Africa and Ecowas – the Economic Community of West African States. It is also worth noting that there was no African presence at Senningen, something that is due to be corrected at the next meeting, scheduled for December 2004. The meeting was convened without any publicity and was concluded without a briefing to the press. The Africa Clearing House is the brainchild of the Eucom – the U.S. European Command, which covers all of Africa, except for Sudan and the Horn. It is arguably one of the most important international security initiatives relating to the African continent that is presently under way. It is certainly the least well known. Aim
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.233 | 0.094 |
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".