Bibliographic record
Abstract
Le terme « infrastructure » évoque spontanément les équipements \nroutiers, ferroviaires, maritimes, le système d’électricité ou le réseau \nhydraulique. En science, les infrastructures de recherche réfèrent aux \ngrands équipements scientiiques (observatoires astronomiques, synchrotrons, \nréseaux de surveillance de l’environnement), aux collections (musées d’histoire naturelle) ou encore aux infrastructures informationnelles \n(Internet et grandes bases de données). Sur le plan théorique, \nla notion d’« infrastructure sociotechnique » a été proposée au milieu \ndes années 1990 par Star et Ruhleder pour étudier l’infrastructure d’un \npoint de vue sociologique, c’est-à-dire du point de vue des pratiques \nassociées à leur développement, cherchant ainsi à dépasser les visions \npurement techniques (voir Objet technique). Les études d’infrastructure \n(infrastructure studies) se sont développées autour de cette notion.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".