Bibliographic record
Abstract
Abstract Alongside the model embellishments Mozart composed for various keyboard works, he also wrote embellishments for contemporary arias including ‘Ah, se a morir mi chiama’ from Lucio Silla, the concert aria ‘Non sò d'onde viene’ K.294 and ‘Cara, la dolce fiamma’ from J.C. Bach's Adriano in Siria. Although these have been overlooked in the critical literature, they shed light on many aspects of Mozart's art of melodic decoration. In this article, I begin by examining these notated operatic embellishments: their textual histories, the styles of elaboration they evince, the pacing with which they unfold, and their motivic construction, as well as their relation to broader trends in Mozart's style. I then explore the embellishments Mozart composed into the texts of his other operas, arguing that these served not only a musical but also an aesthetic purpose, furthering elements of characterisation and drama, particularly in Le nozze di Figaro, Don Giovanni, and Così fan tutte. I end with brief remarks on the challenges facing modern-day interpreters who wish to embellish Mozart's operas.
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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 | 0.005 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".