Bibliographic record
Abstract
More than 1,000 years ago, a goatherd in Ethiopian south-western highlands plucked a few red berries from some young green trees growing there in the forest and tasted them. He liked the flavour and the feel-good effect that followed. Today those self-same berries, dried, roasted and ground, have become the world’s second most popular non-alcoholic beverage after tea. Ethiopian province where it first blossomed “Kaffa” gave its name to coffee. Coffee is the number one foreign exchange earning export commodity of Ethiopia. Almost 2% of the world’s coffee comes from Ethiopia. Well over 60% of the country’s foreign exchange is obtained through the export of coffee. About half of the coffee produced in Ethiopia, is exported to Europe, ¼th to Asia and the rest to North America. It also contributes about 100% of government revenue. it is estimated that area under coffee trees are 679, 147 ha. The annual coffee production of the country ranges from 200-250 thousand tons. A quarter of the population is directly or indirectly engaged in the production, processing and marketing of coffee. Almost 95% of the total production is covered by 2 million small holders and the remaining share of the output goes to the state owned enterprise i.e. Coffee Plantation Development Enterprise About half of the coffee produced is for domestic consumption. There are four main coffee production systems in Ethiopia: forest coffees, garden coffees, traditional small coffee farms and large scale modern plantations. About 35% of the total production is consumed within the producing areas. Coffee ceremony is a strong cultural tradition throughout Ethiopia. Important events are opened with a coffee ceremony. As well, people traditionally gather together over coffee to just enjoy conversation on a regular basis.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".