A study on the trade direction of fresh and dried figs : Export from Afghanistan
Bibliographic record
Abstract
Figs is one of the most important and delicious fruits. Afghanistan produces 24319 tonnes of figs during 2019 (FAO statistics). It is one of the important commodities in export basket of Afghanistan. The major export markets for figs are India, Pakistan USA, Canada and U Arab Emts.The present study aims to quantify the export performance and changing structure of figs exports from Afghanistan. Secondary data on area, production and country wise quantity exports of figs was collected from FAO statistics, and APEDA for a period of 10 years from 2010 to 2019. Compound annual growth rate was computed for studying the trend in area, production, yield, export quantity and export value for figs. Markov chain analysis was attempted to assess the direction of change in exports. Markov chain analysis results showed that, India is the stable market for Afghan figs and U Arab Emts are less stable markets. The major reasons are geographical advantage and good relations for India which gave competitive advantage over other countries with reference to fresh and dried figs export. India is the main country to import figs in the next five years. It shows high value in terms of quantity and percentage which is more than 90 per cent of all Afghanistan’s figs export.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".