Bibliographic record
Abstract
L’une des premières œuvres humoristiques de Debussy est Pierrot (1882), une mélodie répétant sans cesse l’air populaire associé au personnage de la commedia dell’arte : « Au clair de la lune ». Comme de nombreux artistes de son temps, Debussy semble céder à la tentation de se projeter dans le personnage – ce à quoi invite le poème de Banville qu’il met en musique, soulignant cette ambigüité identitaire. Pierrot est aussi l’éternel perdant en amour, Colombine lui préférant toujours Arlequin. Or, Debussy dédie sa mélodie à Marie-Blanche Vasnier, sa première muse, une femme mariée dont il est tombé amoureux, lui offrant une nouvelle occasion de se trouver des points communs avec Pierrot. La musique confirme l’hypothèse de l’autoportrait, puisque Debussy donne un rôle de premier ordre à la note si, qu’il a choisie pour le représenter, correspondant à la dernière syllabe de son nom. Ainsi, derrière l’apparente légèreté, se cache la confession de la souffrance amoureuse de l’artiste.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".