An Analysis of Energy Use and Estimation of a Mechanization Index of Garlic Production in Iran
Bibliographic record
Abstract
This paper studies the energy balance between the input and the output per unit area for garlic in Hamedan province of Iran. In this study, data were collected by using random sampling method for 136 face to face questioners. Results showed that the highest share of energy consumption belongs to chemical fertilizers (41.7%) followed by diesel (13.94%). The results indicated that a total energy input of 40307.89MJ ha-1 was consumed for garlic production. The energy productivity and net energy value were estimated as 0.416 kg MJ-1 and-13477.82MJ ha-1, respectively. The ratio of energy outputs to energy inputs was approximately 0.665. The benefit-cost ratio was estimated as 1.36.mechanization degree (MD) was calculated for plowing and disk border were 100% and 20.65%, as the highest and lowest, respectively. The farms of between two to three hectares with 0.89 highest mechanization index (MI) and those Between one to two hectare with 0.6 lowest MI were remarkable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".