Le projet QDMTL : modéliser les quartiers disparus de Montréal avec des données ouvertes et liées
Bibliographic record
Abstract
Cet article expose la démarche et les résultats d’un projet d’implémentation d’un réseau de données ouvertes et liées. Ce projet porte sur des quartiers disparus de Montréal dans les décennies 1950-1960. À partir de données principalement extraites de documents d’archives, le projet QDMTL propose la modélisation sémantique de ce fonds numérisé, accompagnée de la description du patrimoine bâti des quartiers disparus. Sous la forme d’un ensemble de triplets, le jeu de données produit dans le cadre de ces travaux est exposé au moyen des technologies du Web sémantique. Le projet cherche à établir la faisabilité et la pertinence d’une telle démarche dans le cadre de l’étude des quartiers disparus de Montréal et plus largement pour l’histoire de la ville.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".