Bibliographic record
Abstract
Parfois considérées avec condescendance, les Mémoires que G.-Eugène Haussmann rédige à la fin de sa vie ne manquent pourtant pas d’intérêt. Au fil des pages du premier volume, d’Yssingeaux à Saint-Girons en passant par Nérac et Blaye, on suit les voyages pittoresques d’un jeune sous-préfet chevauchant à la rencontre de ses administrés. On dirait des récits d’excursions de l’un de ces « géographes » du milieu du XIXe siècle qui frayent le chemin d’Élisée Reclus. Curiosité et acuité du regard sur les paysages traversés et l’activité des hommes qui les peuplent, précision des itinéraires, justesse des notations géologiques et morphologiques… Haussmann mesure ses connaissances acquises au collège Henri IV à la rigueur scientifique de son temps, tout en contant avec verve les aventures qui émaillent sa vie d’explorateur à la rencontre des Gascons et des ours.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".