Bibliographic record
Abstract
C’est sur le thème pluriel de territoire que j’ai esquissé un bref portrait du compositeur québécois Serge Arcuri. L’idée du territoire est prise ici au sens propre comme au sens figuré. Je parle de celui défriché par son mentor, Gilles Tremblay, un territoire partagé par tant de compositeurs du Québec. De celui aussi qui forge l’identité personnelle, créatrice et poétique. Ce texte se veut le compte rendu d’une rencontre cordiale, sans formalités, qui a eu lieu à l’automne 2016 et au cours de laquelle nous avons discuté à bâtons rompus du métier d’Arcuri, du milieu musical dans lequel il évolue, de son parcours hors normes, de ses études au Conservatoire de musique de Montréal, des influences qui ont pu façonner sa personnalité, des éléments qui constituent son langage, en plus de jeter un oeil à l’intérieur de quelques-unes de ses oeuvres pivots. En somme, un tour d’horizon du territoire Arcuri.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 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".