Analisis Manajemen Risiko untuk Perusahaan Non-Keuangan United Grain Growers (UGG)
Bibliographic record
Abstract
United Grain Growers Company (UGG), which is a company engaged in agriculture in Canada. UGG risk management practices that are innovative enough to bring the award of best practices by insuring exposure not previously been insured, such as weather risks that are integrated with other risks. For that level of climate change risk analysis will determine the level of harvest delivery volume by analyzing the retention side, derivatives, and insurance. Keywords : UGG, Risk Management, Risk Weather, Retention Weather, Weather Derivatives, Insurance Abstrak Perusahaan United Grain Growers (UGG), yaitu perusahaan yang bergerak di bidang pertanian di Kanada. Praktik manajemen risiko UGG yang cukup inovatif mendatangkan penghargaan praktik terbaik dengan mengasuransikan eksposur yang sebelumnya belum pernah diasuransikan, seperti risiko cuaca yang diintegrasikan dengan risiko lainnya. Untuk itu tingkat analisis risiko perubahan cuaca sangat menentukan tingkat volume pengiriman panen dengan menganalisis dari sisi retensi, derivatif, dan asuransi. Kata Kunci : UGG, Manajemen Risiko, Risiko Cuaca, Retensi Cuaca, Derivatif Cuaca, Asuransi.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".