Bibliographic record
Abstract
L’Observatoire des Sédiments du Rhône (OSR) a été créé en 2009 à la suite de questions qui ont émergé dans le cadre du plan Rhône. Sur le Rhône, du Léman à la Méditerranée, soit un linéaire de plus de 500 km, cet observatoire a pour mission de produire, rassembler et gérer des données visant à caractériser les stocks et les flux sédimentaires, ainsi que les pollutions associées à ces sédiments.L’OSR est un programme de recherche financé au titre du Plan Rhône et bénéficie du soutien du Fond Européen pour le Développement Régional. L’OSR est un programme de recherche regroupant scientifiques (CNRS, INRAE, ENTPE, IRSN, Ifremer) et les principaux gestionnaires du fleuve (DREAL, Agence de l’Eau, la CNR, les régions Auvergne Rhône-Alpes, Provence-Alpes-Côte d’Azur et Occitanie, et EDF). Il constitue l’un des observatoires de la Zone Atelier du Bassin du Rhône (ZABR).Sites expérimentauxRéseau de mesure des flux de l'OSRCe site expérimental regroupe les suivis par les différents partenaires de l'OSR des débits, des concentrations en matières en suspension et des concentrations en micropolluants sur le Rhône et ses affluents.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".