(Re) Voir l'intervention de Cécile Asanuma-Brice dans le séminaire « Approches urbaines et anthropocènes », porté par la chaire conjointe de recherche Université d’Ottawa - Ecole urbaine de Lyon
Bibliographic record
Abstract
https://youtu.be/pAf5Gpblxww Le premier volet du séminaire de la chaire conjointe de recherche Université d’Ottawa et Ecole urbaine de Lyon « Approches urbaines et anthropocènes » s'est déroulé en visioconférence le 1er avril 2021 avec Cécile Asanuma-Brice (CNRS, chercheuse associée du CRJ) sur le thème « Fukushima, 10 ans après : la réouverture de la zone d'évacuation en question ». Le 11 mars 2011, au large des côtes de l’île japonaise de Honshu, un séisme de magnitude 9,1, doublé d’un tsu...
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.059 | 0.017 |
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".