Evaluating Greenhouse Tomato and Pepper Input Efficiency Use in Kosovo
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Determinants of vegetable production input efficiency affect a Kosovar farmer’s decision to contribute to the agricultural sector. This study evaluates the input efficiency of greenhouse tomato and pepper farms in Kosovo. Using data collected from farm surveys, we conducted an input-oriented data envelopment analysis (DEA) to empirically assess input efficiency. Second, linear regression analysis was used to investigate what farm variables predict greenhouse tomato and pepper technical efficiency (TE). The DEA results indicated that, among the seven regions in Kosovo, Prizren emerged as the most efficient greenhouse tomato-producing region with a mean efficiency of 0.83 (on a scale of 0 to 1.00). Prishtina followed with a mean efficiency of 0.80. In the production of greenhouse peppers, Prishtina was the most efficient region with a mean efficiency of 0.99. Ferizaj followed with a mean efficiency of 0.93. Conclusions about farm characteristics that explain differences in efficiency were sensitive to model specification. Nevertheless, depending on the structural and operational characteristics of the greenhouse tomato and pepper farms, there is an opportunity for the technically inefficient farms and regions to improve their use of inputs.
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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 | 0.015 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it