Bibliographic record
Abstract
Gesho is a multipurpose crop as its all parts harvested and utilized. The study was conducted to analyze the trend of production and export of gesho in Ethiopia. Secondary data on production and export of gesho were used. The study identify the total hectare of land under gesho production and the total volume of production has increased with a compound growth rate of 3% and 4% respectively during the study period; while the productivity of the crop gesho has shown no change during the same period. Ethiopia exports on average 371,091 kg of gesho and gesho products to various countries and incurred birr 8,250,427. Israel, Burundi, Hong Kong, South Africa, Spain, Sudan, Sweden, Swaziland, Great Britain, United States, United Arab Emirates, Djibouti, Iceland, Albania, Canada, Greece, Germany, Italy, United Kingdom, Netherlands, Australia, Switherland, Norway and China are countries Ethiopian gesho and gesho products are destined during the study period. Israel and Sudan are the highest volume recipient countries for Ethiopian gesho and gesho products with the percentage share of 22 % and 72 % respectively. The total volume of export destined to Sudan during the study period is 5, 354, 567 kg and the total volume exported to the second large recipient country Israel has been 1,627,631 kg. Great Bretain, Hong kong and Norway are the destination countries from which highest value/kg from gesho export is received. Ethiopia earn birr 322/kg and birr 304/kg from export of gesho to Great Britain and Hong kong respectively. The export value of 1kg of gesho per kg for export destined to largest recipient country of Ethiopian gesho export- Sudan is birr 24.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".