The Strategies in the Battles and Struggles of Prophet Muhammad: How It Can Be Applied in Modern Business
Bibliographic record
Abstract
The main purpose of this study is to investigate the strategies of Prophet Muhammad PBUH in wars and struggles, and how they are practiced now in contemporary businesses and organizations. This study is interested to read the biography oh Prophet Muhammad, the strategies which He made during wars and migration, their execution and consequences and how modern businesses adopt these strategies to improve the organizational graph. The purpose of this paper is thoroughly study the biography of beloved Prophet and to recall the Holy Prophet (PBUH) strategies, which He used during his life and mostly implemented in wars and battles for victory. The concept of making strategies is came from Him, which now world widely followed by everyone even by Muslims or not Muslims. Prophet presented the thought of environmental Analysis, for the purpose to get information from external and internal environment about enemies. This analysis is applicable upon all organizations especially Military. Now it is executed as risk management, to prevent from sudden unfortunate events in future. In short, all the strategies, which are now run-through all organizations are basically belongs to Holy Prophet
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".