The Rivalry for Galich between Daniil Romanovich and Mikhail Vsevolodovich (1235 – 1245).
Bibliographic record
Abstract
The rivalry for Galich between the Ol’govichi of Chernigov and the Romanovichi of Vladimir in Volyn’ began during the first decade of the thirteenth century. In 1235 prince Mikhail Vsevolodovich judged that the time was propitious for him to occupy Galich. After his victory near Torchesk, therefore, Mikhail occupied Kiev and Galich. The Ol’govichi also achieved diplomatic in addition to military victories over the Romanovichi. The Tatar invasion of Ryazan’ in the winter of 1237/8 was probably the most important reason why Mikhail failed to maintain his hold over southwestern Rus’. Mikhail was unable to organize a consolidated defense against the expected Tatar attack because the other princes refused to join him. Meanwhile, Daniil, having concluded peace with the Tatars, strengthened his position. In 1245 Daniil visited Saray and Khan Baty gave him the yarlyk to rule Galich. His action quashed any hope Mikhail may have had of repossessing the town. Keywords: Galicia, Daniil Romanovich, Mikhail Vsevolodovich, chronicle, Tatar invasion. Normal 0 false false false RU X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Обычная таблица; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:Calibri,sans-serif;}
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".