Aude Ameille, Pascal Lécroart, Timothée Picard & Emmanuel Reibel (eds), Opéra et cinéma
Bibliographic record
Abstract
Dans le numéro spécial de l'Avant-scène opéra (n° 98, 1987, p. 6) consacré aux rapports entre opéra et cinéma, Ermanno Comuzio pouvait écrire : Un vent de folie souffle sur l'opéra, tant à la scène qu'à l'écran.Plus qu'une mode, c'est un must, une obligation sociale, à tous les niveaux.Les hommes de spectacle font des pieds et des mains pour réaliser des mises en scène d'opéra ; les chefs d'orchestre défendent des alliances jadis impensables avec des auteurs qui ne se limitent plus à faire évoluer des groupes sur scène ou à suggérer des mouvements aux chanteurs, mais proposent des 'interprétations globales' ; les impresarios ne savent plus où donner de la tête ; les cinéastes enfin, meurent d'impatience de porter les mélodrames à l'écran.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".