Evaluation of Total Factors Productivity of Three Ilam Major Products (Wheat, Corn and Cucumbers)
Bibliographic record
Abstract
<p class="zhengwen"><span lang="EN-GB">The purpose of this study is to evaluate the productivity of total factors Production(water, land and labor) of three Ilam major products which are wheat, corn and cucumber. This study is calculated by conventional methods of measuring productivity and production function of Cobb- Dougles. The results of this study showed that the average productivity cost (during 2000-2009) of lading the ground for irrigated farm is 111.727$ and for dry farm it is 17.468$.the average productivity in this period for lading the labors in irrigated farm of wheat is 2.932 $and for dry land ,it is 1.237 $. The Average productivity of the land for cultivation of maize is 1356600 </span><span lang="EN-GB">Riyals and for work force is 26.51$.The obtained average productivity of labor and cucumber lands during this period is 1.600 and 208.833$.</span></p><p class="zhengwen"><span lang="EN-GB">Water productivity in the production of Cucumber for Dareshahr and Sarableh cities is respectively 1.112 and 0.437.Average productivity of water in cucumber productions is0.774. The differences of corn productivity of the two cities is almost the same but Mehran and Aivan have the highest and the lowest productivity in Ilam, Mehran has 0.675 and Aivan has 0.274 of productivity. The average productivity is 0.416</span><span lang="EN-GB"> .</span><span lang="EN-GB">The ratio of the highest and lowest value of the obtained product from each unit of water in Dareshahr is more than 4/5 times. Thus the value of the water product in the cultivation of cucumbers is over 1.729 $, while this number for wheat is only 0.367 $.</span></p>
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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 | 0.002 | 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 | 0.000 | 0.000 |
| 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 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".