Bibliographic record
Abstract
Francesco Sforza was a pivotal figure in the state system of Italy in the 15th century. The son of a prominent condottiere, Muzio Attendolo Sforza, he inherited his father’s company of soldiers in 1424 and became one of the foremost condottieri of his time in his own right. In 1434 he took over much of the province of the Marche in the Papal States and held on as lord there until he was finally driven out in 1447, shortly before the death of his father-in-law, Filippo Maria Visconti, Duke of Milan. Although his relations with Visconti, before and after he married Visconti’s daughter, Bianca Maria, had often been bad, when Visconti died without legitimate heirs, Sforza claimed the dukedom. He had to conquer the duchy before he was accepted in Milan as duke in 1450. Despite the legitimacy of his rule continuing to be under question, Sforza became the most influential statesman in Italy, through the use of the impressive diplomatic network he built up rather than through military interventions. The records created and preserved by his efficient chancery constitute a major source for the history of Italy in the mid-15th century. References to him abound in the historiography of Renaissance Italy, but there are not a great many works focused on him, and only a few in English.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.022 |
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".