Bibliographic record
Abstract
The aim of the present study is to develop a model for determining the optimal capacity of production in milk and dairy industries companies indicating on raw materials supply chain in Shevin Company in an attempt to achieve the maximum profit sing linear planning techniques.The study is applied and descriptive in terms of the goal and quality of data collection, respectively.The reason of being applied is that the implications if the research result are employed to improve the product planning of production unit.The decision-making variables having to do with linear planning model involves types of buttermilk, yoghurt, and produced milk.To answer the linear planning pertinent to the problem of determining optimal combination of produced products of the considered unit, LINGO 14 software was utilized.It was found in the present study that the expenses having to with production line, penetration coefficient, available capital, raw materials of buttermilk, raw materials of milk, mil advertisements, buttermilk distribution, and produced wastes are higher than needed.Also, the optimum value of the target function is 249556.7.
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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 | 0.000 | 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) | 0.996 | 0.970 |
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; both teacher heads agree on what is shown here.
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".