Bibliographic record
Abstract
Avec plus de 150 spécialistes en acoustique à travers le monde, WSP Global possède une des plus large expertise en acoustique à l’international. Nos spécialistes sont basés dans les villes les plus importantes à travers le monde afin de s’assurer que des équipes locales puissent se mobiliser rapidement tout en tirant profit de notre réseau d’expériences globales. Notre taille nous permet aussi de faire profiter nos clients d’expertises techniques pointues dans divers domaines spécifiques de l’acoustique. Nous pouvons donc étudier tous les aspects d’un projet. Nous avons l’expertise de fournir des solutions de bout en bout, de l’étude d’impact durant la phase de planification, à travers le design des détails acoustiques des projets, jusqu’au suivis acoustiques et au dimensionnement de solutions de réduction du bruit durant la construction, l’exploitation ou même le démantèlement. Nous fondons notre méthode sur l’excellence technique dans nos solutions mais nous avons la réputation de remettre en cause le statu quo et de fournir une expertise créative, pragmatique, durable et concurrentielle.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".