Review of the status of African lion (Panthera leo) in Ethiopia
Bibliographic record
Abstract
African lion (Panthera leo), is an important species in the Ethiopian ecosystems. However, significant lion populations and their suitable habitats in many of their former ranges in Ethiopia have declined over time due to socioeconomic uncertainty and the resulting ecological imbalances. Despite this general trend, it is equally noted that there is a lack of verifiable data which depicts the past and current status of African lions. Thus, very little is known about the species in question in most of its ranges. Available published and unpublished reports and manuscripts on the target species were reviewed in order to examine and document the status of the African lion in Ethiopia. From our review, we concluded that the lion numbers are still low and declining whilst considerable ranges have been identified through the field assessments conducted in the last two decades. African lions in Ethiopia have been under serious threat from various anthropogenic activities and it is therefore recommended to effectively implement the national conservation action plan for lion and undertake further field assessment on its habitats. This study suggests the establishment of a national Red list category for the threatened species based on the final reports of our assessments. Key words: Trends, abundance, distribution, threats, conservation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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".