Bibliographic record
Abstract
Après une enfance paysanne et des études d’agronomie, Honda Seiroku (1862-1952) approfondit la sylviculture en Allemagne de 1890 à 1892. Il fait partie de l’élite éclairée de l’ère Meiji, époque d’introduction des techniques occidentales. En 1893, il devient enseignant et modernise la gestion forestière du Japon. En 1901, il prend en charge le projet du parc Hibiya à Tōkyō, premier parc public à valeur archétypale. Il oriente le projet autour du sanctuaire Meiji (1915) vers la création d’une forêt en pleine ville, considérée comme exemplaire aujourd’hui. Il est à l’origine de la conception de nombreux parcs urbains ainsi que des parcs nationaux (1930). À travers les réalisations de Honda, apparaissent les spécificités de son parcours de forestier-paysagiste, objet d’une réception renouvelée aujourd’hui.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".