Espace et humanités numériques : le fort de Chambly et l’héritage de Vauban en Amérique du Nord
Bibliographic record
Abstract
Cet article propose de survoler la méthodologie du projet Vauban en Amérique ? qui fit l’utilisation—entre autres—de la photogrammétrie et des systèmes d’information géographique (SIG) afin de bonifier l’étude de l’héritage de Vauban Plus précisément, c’est le fort de Chambly qui a servi de banc d’essai à nos expérimentations. Ainsi, Vauban en Amérique ? est une initiative d’étudiants à la maîtrise en informatique appliquée à l’histoire à l’Université de Sherbrooke. Sous la bannière Historiamatica , une plateforme web qui regroupe différentes initiatives en humanités numériques parmi les étudiants et étudiantes en histoire, les membres du projet Vauban ont créé une application web permettant de visualiser les différents types de structures défensives.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".