Bibliographic record
Abstract
<p>Milk marketing in rural area of Dhofar Region face a lot of difficulties and constrains by individual small scale farmers due to the lack of facilities and access to market. Therefore, farmers reduce their cow and camel milk production and group their animal into three or four groups to be milked in alternative days. Government Authorities decided to establish Milk Collection Centers to facilitate milk marketing and provide raw milk to Dairy industries. A risk analysis for the investment in milk collection centers on rural area of Dhofar Region was conducted in this study. The results showed that all MCC investments had a positive NPV except Shahbi Aseab Center. The study indicates there is a direct relationship between total milk collected, milk price, distant between MCC and Dairy plan and investment profitability. The study revealed an inverse relation between animal population at MCC zone and risk. The probability of achieving returns lower than the opportunity cost was highest for MCC located far from dairy plant which process and market dairy products. Risk premium for four MCC has been calculated relative to Salalah MCC (preferred location) and (Garoun Hirity MCC) was found as preferred MCC location and risk efficiency. In order to make the investment in MCC more attractive, the Government incentives need to be offered to farmers to increase milk production and improve raw milk quality. However, this approach might make investments in bulk milk collection centers feasible. Thus, a recommendable strategy for a successful modernization of the Oman dairy sectors inbound logistics would be to promote an increase in the volume of the milk produced per farm and improve marketing facilities through MCC.</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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| 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".