Premières représentations du Huyapari (alias Orénoque) (1498-1552) : la quête de Meta et ses revers
Bibliographic record
Abstract
Les grands fleuves américains ont plus été des obstacles que des voies de communication pour les conquérants espagnols ou portugais. Leur gigantisme et le milieu naturel amazonien s’agissant de l’Amazone et de l’Orénoque, ont provoqué un discours géographique brouillé, des expériences le plus souvent malheureuses, une cartographie spéculative et la prolifération de mirages aurifères. Les réalités hydrographiques et ethnographiques du bassin de l’Orénoque ont été perçues de façon fragmentaire, incertaine, parfois même absorbées par son voisin géant pendant tout XVIe siècle : c’est l’émergence de cette confuse géographie fluviale que nous souhaitons analyser, pour en montrer à la fois les acquis, les attentes et les déboires.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".