El papel de los neurocirujanos cubanos en el desarrollo de la Neurocirugía en Etiopía
Bibliographic record
Abstract
Ethiopia, a nation of more than 90 million people faces both great challenges and great opportunities in the pursuit of improved national access to health care. In addition to the daunting of socioeconomic challenges, the development of medical knowledge in Ethiopia also has been hindered by physician emigration. Approximately 15 percent of Ethiopian physicians now are practicing in the United States, Canada or Australia, with another significant portion serving other portions of Africa and the Middle East. Until the end of 1990, there were at least two Cuban neurosurgeons among the huge number of Cuban physicians and paramedics that constitute “Brigada Medica Cubana en Etiopia Socialista”. It was only by the end of the downfall of Socialist regime, three Ethiopian Neurosurgeons two of them trained in Cuba started providing basic Neurosurgical services. The evolution of the development of Neurosurgery is described in four periods or era in which the role of the Cuban part is strongly emphasized.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".