Bibliographic record
Abstract
D’octobre 1951 à mai 1952, Serge Garant séjourne à Paris en compagnie de ses amis Wilfrid Lemoyne et Suzanne Gagnon. Tout en découvrant les trésors culturels de la capitale française, il assiste aux célèbres cours d’analyse donnés par Olivier Messiaen au Conservatoire national supérieur de musique de Paris. Il prend également des leçons d’écriture auprès d’Andrée Vaurabourg-Honegger, l’une des pédagogues les plus respectées de la capitale française. Cette période d’apprentissage sera marquante dans le développement du compositeur, comme en font foi plusieurs lettres et témoignages de Garant, de même que les oeuvres composées durant cette période. Cet article vise à mettre en lumière les points saillants du séjour de Garant à Paris, par exemple la découverte des oeuvres de Messiaen et de Pierre Boulez, et l’impact de cette expérience sur les activités subséquentes du compositeur québécois.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".