Bibliographic record
Abstract
Ce mémoire analyse cinq pièces par Matthew Lane basées sur des poèmes québécois variés, afin d’expliquer plusieurs façons d'utiliser la poésie comme inspiration et matériel pour la musique, hors des choix traditionnels (chansons, symphonies à programme). Il comprend l'analyse des techniques utilisées pour la cohabitation des mondes instrumentaux et électroniques afin de créer un résultat musical convaincant. Il discute aussi de la manière dont le compositeur s’est servi de techniques de Composition Assistée par Ordinateur (COA). Les pièces explorées sont : 1) Le Lézard Vert, basée sur un poème de Dany Laferrière (pour cor et bande) 2) L’Écho bouge beau, basée sur des poèmes de Nicole Brossard (pour ensemble de chambre et électroniques live) 3) Saisie, basée sur des poèmes de Pierre Nepveu (pour chœur, 3 récitants, et bande) 4) L’Héritage, basée sur un poème de Marc Vaillancourt (pour orchestre de chambre et sons déclenchés) 5) Sans titre à Montréal, basée sur un poème de Louis Carmel (pour quatuor à cordes)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".