Les archives européennes et les expéditions de Cartier et de Roberval
Bibliographic record
Abstract
C’est bien connu, l’archéologie et l’histoire sont liées de façon irrémédiable. Si des fouilles s’imposent face à un site mal documenté ou très ancien, des recherches dans les sources manuscrites et imprimées sont nécessaires, surtout si les sources matérielles sont lacunaires. L’interaction entre ces deux disciplines est constante. C’est-à-dire que, chaque fois que l’on dégage des vestiges, de nouvelles questions sont soulevées, auxquelles l’on essaie de répondre via un soutien documentaire. Et, lorsque les sources manuscrites sont adéquates et précises, il est possible de faire de nouvelles trouvailles archéologiques. C’est ce type de situation à laquelle nous sommes confrontés sur le site de Cap-Rouge, où les sources manuscrites peuvent aider à préciser les lieux, nous éclairer sur la présence de certains artefacts ou comprendre la fonction d’objets inconnus.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".