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Record W6925206152 · doi:10.17180/obs.osr

Observatoire des Sédiments du Rhône

2024· dataset· fr· W6925206152 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen MIND · 2024
Typedataset
Languagefr
Field
Topic
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsContext (archaeology)Statistical analysisWest indies

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.839
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0050.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1170.956

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.

Opus teacher head0.100
GPT teacher head0.349
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations13
Published2024
Admission routes1
Has abstractyes

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