The Forces Opposed to Abu Al-Abbas the Slaughter and the Mechanism of Dealing with Them
Bibliographic record
Abstract
The Abbasid Call has declared its victory and the end of the Umayyad state and the beginning of the era of a new state, the Abbasid state. Abu Abbas, the first of the Abbasid caliphs, bore the burden of leadership over Ibrahim the imam, as well as the obstacles to its establishment and the various reactions that were issued in word and deed.However, leaders in history differ in their response to attitudes from one leader to another, the presence of the opposition forces in the Abbasid state showed the caliphs mechanism of dealing with the various positions and the extent of their knack and intelligence in dealing with them, and show the hidden aspects of the personality of each of the caliphs.Perhaps Abu Abbas the slaughter was the most prominent caliphs who suffered from the large number of opposition forces where he faced a large number of forces that threatened to remain in power, but his will and political intelligence managed to address them.Many scholars have studied the Umayyads or the ovaries or the revolutions of the Shiites in the Abbasid period, as many have studied the leaders of such as Abu Musallam Al-Kharasani and Abu Salamah, but Abu Abbas the slaughter did not have a large presence in these studies, and this research specialized about the methods and ways that Abu Abbas the slaughter used to deal with those different forces.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".