Bibliographic record
Abstract
La charge de cavalerie constitue sans doute un angle d’étude essentiel pour envisager l’emploi du cheval dans le cadre militaire à l’époque Moderne. Or l’allure est un des principes fondamentaux de la charge. Parce qu’il s’agit tout d’abord d’un facteur qui intervient pour une part importante dans le succès ou l’échec. Parce qu’elle est d’autre part déterminée par des éléments complexes et multiples, extérieurs à la simple capacité physique des chevaux. L’entraînement des hommes et des montures, le poids des armes défensives, le choix des armes à feu ou des armes blanches sont autant d’éléments qui expliquent que les cuirassiers du début de la guerre de Trente Ans allaient au trot et que les cavaliers de Charles XII chargeaient au galop. Au-delà de la simple estimation de la vitesse, l’analyse des mécanismes qui déterminent le choix de l’allure et expliquent la préférence pour l’une ou l’autre à un moment donné permet de mieux comprendre le déroulement des charges de cavalerie.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.932 | 0.926 |
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; the direct Gemma label and the distilled Codex classifier 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".