Infrastructures de transports terrestres, paysages et écosystèmes (ITTECOP)
Bibliographic record
Abstract
Inscrit dans le cadre du bilan du PREDIT 4 auquel le programme de recherche ITTECOP est associé sur le volet « impact environnemental des transports », le colloque des 26 et 27 septembre est l’occasion de présenter simultanément les quinze projets de recherches soutenus par le programme mais aussi ceux, plus opérationnels, qui y sont associés. Autour de la thématique des infrastructures de transports terrestres, trois sessions de restitution avec les thématiques écosystèmes, paysages et projets de territoires sont organisées. Une session atelier permet d'explorer les thèmes transversaux aux projets de recherche qui participent aussi à la réussite de ces derniers : l'animation interne des projets, les outils et leurs utilisations et la valorisation. Enfin, des sessions posters viennent compléter l'ensemble.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.019 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.468 | 0.059 |
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; both teacher heads agree on what is shown here.
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".