Bibliographic record
Abstract
Des Images oubliées aux Reflets dans l’eau, une grande majorité de la musique de Claude Debussy est remplie d’images et de tableaux sonores. L’oeuvre debussyste est d’ailleurs amplement citée comme préexistante dans le cinéma, tout genre confondu, et ce depuis le muet, notamment pour les scènes de plein air, jusqu’à la période contemporaine. Debussy est musicien de la nature, du voyage, d’effets de lumière dans l’eau, voire du monde de l’enfance, mais bon nombre de ses oeuvres (« Nuages », Pelléas et Mélisande, Le Martyre de Saint-Sébastien ou son opéra inachevé La Chute de la maison Usher) sont également autant de manifestations de la mort et de la peur. L’ambition de cet article est de montrer en quoi des compositeurs comme Dimitri Tiomkin, Franz Waxman, Bernard Herrmann, Jerry Goldsmith ou encore Alejandro Amenábar sondent le langage debussyste pour enrichir le paratexte de leurs partitions destinées à des films comportant une dimension fantastique sombre, estompant ainsi la frontière qui existe entre eros et thanatos, ou encore entre le monde des morts et celui des vivants.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| 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".