Cancer care in Needle Hospital, Hargeisa, Somaliland
Bibliographic record
Abstract
Somaliland is an autonomous region in the northern part of Somalia that declared its independence in 1991. It is a low-income country (LIC) with a population size of 5.7 million with a gross domestic product per capita of $775. Health services are delivered by public, private and non-governmental organisations. The public health care system in Somaliland is facing huge challenges. Seven percent of the population suffers from non-communicable diseases, but data on cancer incidence and mortality are not available. Much of the emphasis in public health has been placed on primary care and maternal and child health. There is still a large gap in cancer prevention, early detection and screening in the country. Additionally, there is no cancer registry or published data on cancer. Currently, there are a few private hospitals that provide chemotherapy services in Somaliland of which Needle Hospital is one. Services provided in this hospital include medical oncology for all solid tumours, palliative care, follow-up and cancer health education. The hospital provides services for patients from Somaliland and neighbouring countries including Djibouti, Somalia and Ethiopia. As a new oncology clinic in an LIC, the clinic is facing many challenges, like the absence of a multidisciplinary tumour board, presentation of patients at the advanced stage of tumours and poor cancer awareness in the general population.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".